most interesting research areas in computer science

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500+ Computer Science Research Topics

Computer Science is a constantly evolving field that has transformed the world we live in today. With new technologies emerging every day, there are countless research opportunities in this field. Whether you are interested in artificial intelligence, machine learning, cybersecurity, data analytics, or computer networks, there are endless possibilities to explore. In this post, we will delve into some of the most interesting and important research topics in Computer Science. From the latest advancements in programming languages to the development of cutting-edge algorithms, we will explore the latest trends and innovations that are shaping the future of Computer Science. So, whether you are a student or a professional, read on to discover some of the most exciting research topics in this dynamic and rapidly expanding field.

Computer Science Research Topics

Computer Science Research Topics are as follows:

Using machine learning to detect and prevent cyber attacks
Developing algorithms for optimized resource allocation in cloud computing
Investigating the use of blockchain technology for secure and decentralized data storage
Developing intelligent chatbots for customer service
Investigating the effectiveness of deep learning for natural language processing
Developing algorithms for detecting and removing fake news from social media
Investigating the impact of social media on mental health
Developing algorithms for efficient image and video compression
Investigating the use of big data analytics for predictive maintenance in manufacturing
Developing algorithms for identifying and mitigating bias in machine learning models
Investigating the ethical implications of autonomous vehicles
Developing algorithms for detecting and preventing cyberbullying
Investigating the use of machine learning for personalized medicine
Developing algorithms for efficient and accurate speech recognition
Investigating the impact of social media on political polarization
Developing algorithms for sentiment analysis in social media data
Investigating the use of virtual reality in education
Developing algorithms for efficient data encryption and decryption
Investigating the impact of technology on workplace productivity
Developing algorithms for detecting and mitigating deepfakes
Investigating the use of artificial intelligence in financial trading
Developing algorithms for efficient database management
Investigating the effectiveness of online learning platforms
Developing algorithms for efficient and accurate facial recognition
Investigating the use of machine learning for predicting weather patterns
Developing algorithms for efficient and secure data transfer
Investigating the impact of technology on social skills and communication
Developing algorithms for efficient and accurate object recognition
Investigating the use of machine learning for fraud detection in finance
Developing algorithms for efficient and secure authentication systems
Investigating the impact of technology on privacy and surveillance
Developing algorithms for efficient and accurate handwriting recognition
Investigating the use of machine learning for predicting stock prices
Developing algorithms for efficient and secure biometric identification
Investigating the impact of technology on mental health and well-being
Developing algorithms for efficient and accurate language translation
Investigating the use of machine learning for personalized advertising
Developing algorithms for efficient and secure payment systems
Investigating the impact of technology on the job market and automation
Developing algorithms for efficient and accurate object tracking
Investigating the use of machine learning for predicting disease outbreaks
Developing algorithms for efficient and secure access control
Investigating the impact of technology on human behavior and decision making
Developing algorithms for efficient and accurate sound recognition
Investigating the use of machine learning for predicting customer behavior
Developing algorithms for efficient and secure data backup and recovery
Investigating the impact of technology on education and learning outcomes
Developing algorithms for efficient and accurate emotion recognition
Investigating the use of machine learning for improving healthcare outcomes
Developing algorithms for efficient and secure supply chain management
Investigating the impact of technology on cultural and societal norms
Developing algorithms for efficient and accurate gesture recognition
Investigating the use of machine learning for predicting consumer demand
Developing algorithms for efficient and secure cloud storage
Investigating the impact of technology on environmental sustainability
Developing algorithms for efficient and accurate voice recognition
Investigating the use of machine learning for improving transportation systems
Developing algorithms for efficient and secure mobile device management
Investigating the impact of technology on social inequality and access to resources
Machine learning for healthcare diagnosis and treatment
Machine Learning for Cybersecurity
Machine learning for personalized medicine
Cybersecurity threats and defense strategies
Big data analytics for business intelligence
Blockchain technology and its applications
Human-computer interaction in virtual reality environments
Artificial intelligence for autonomous vehicles
Natural language processing for chatbots
Cloud computing and its impact on the IT industry
Internet of Things (IoT) and smart homes
Robotics and automation in manufacturing
Augmented reality and its potential in education
Data mining techniques for customer relationship management
Computer vision for object recognition and tracking
Quantum computing and its applications in cryptography
Social media analytics and sentiment analysis
Recommender systems for personalized content delivery
Mobile computing and its impact on society
Bioinformatics and genomic data analysis
Deep learning for image and speech recognition
Digital signal processing and audio processing algorithms
Cloud storage and data security in the cloud
Wearable technology and its impact on healthcare
Computational linguistics for natural language understanding
Cognitive computing for decision support systems
Cyber-physical systems and their applications
Edge computing and its impact on IoT
Machine learning for fraud detection
Cryptography and its role in secure communication
Cybersecurity risks in the era of the Internet of Things
Natural language generation for automated report writing
3D printing and its impact on manufacturing
Virtual assistants and their applications in daily life
Cloud-based gaming and its impact on the gaming industry
Computer networks and their security issues
Cyber forensics and its role in criminal investigations
Machine learning for predictive maintenance in industrial settings
Augmented reality for cultural heritage preservation
Human-robot interaction and its applications
Data visualization and its impact on decision-making
Cybersecurity in financial systems and blockchain
Computer graphics and animation techniques
Biometrics and its role in secure authentication
Cloud-based e-learning platforms and their impact on education
Natural language processing for machine translation
Machine learning for predictive maintenance in healthcare
Cybersecurity and privacy issues in social media
Computer vision for medical image analysis
Natural language generation for content creation
Cybersecurity challenges in cloud computing
Human-robot collaboration in manufacturing
Data mining for predicting customer churn
Artificial intelligence for autonomous drones
Cybersecurity risks in the healthcare industry
Machine learning for speech synthesis
Edge computing for low-latency applications
Virtual reality for mental health therapy
Quantum computing and its applications in finance
Biomedical engineering and its applications
Cybersecurity in autonomous systems
Machine learning for predictive maintenance in transportation
Computer vision for object detection in autonomous driving
Augmented reality for industrial training and simulations
Cloud-based cybersecurity solutions for small businesses
Natural language processing for knowledge management
Machine learning for personalized advertising
Cybersecurity in the supply chain management
Cybersecurity risks in the energy sector
Computer vision for facial recognition
Natural language processing for social media analysis
Machine learning for sentiment analysis in customer reviews
Explainable Artificial Intelligence
Quantum Computing
Blockchain Technology
Human-Computer Interaction
Natural Language Processing
Cloud Computing
Robotics and Automation
Augmented Reality and Virtual Reality
Cyber-Physical Systems
Computational Neuroscience
Big Data Analytics
Computer Vision
Cryptography and Network Security
Internet of Things
Computer Graphics and Visualization
Artificial Intelligence for Game Design
Computational Biology
Social Network Analysis
Bioinformatics
Distributed Systems and Middleware
Information Retrieval and Data Mining
Computer Networks
Mobile Computing and Wireless Networks
Software Engineering
Database Systems
Parallel and Distributed Computing
Human-Robot Interaction
Intelligent Transportation Systems
High-Performance Computing
Cyber-Physical Security
Deep Learning
Sensor Networks
Multi-Agent Systems
Human-Centered Computing
Wearable Computing
Knowledge Representation and Reasoning
Adaptive Systems
Brain-Computer Interface
Health Informatics
Cognitive Computing
Cybersecurity and Privacy
Internet Security
Cybercrime and Digital Forensics
Cloud Security
Cryptocurrencies and Digital Payments
Machine Learning for Natural Language Generation
Cognitive Robotics
Neural Networks
Semantic Web
Image Processing
Cyber Threat Intelligence
Secure Mobile Computing
Cybersecurity Education and Training
Privacy Preserving Techniques
Cyber-Physical Systems Security
Virtualization and Containerization
Machine Learning for Computer Vision
Network Function Virtualization
Cybersecurity Risk Management
Information Security Governance
Intrusion Detection and Prevention
Biometric Authentication
Machine Learning for Predictive Maintenance
Security in Cloud-based Environments
Cybersecurity for Industrial Control Systems
Smart Grid Security
Software Defined Networking
Quantum Cryptography
Security in the Internet of Things
Natural language processing for sentiment analysis
Blockchain technology for secure data sharing
Developing efficient algorithms for big data analysis
Cybersecurity for internet of things (IoT) devices
Human-robot interaction for industrial automation
Image recognition for autonomous vehicles
Social media analytics for marketing strategy
Quantum computing for solving complex problems
Biometric authentication for secure access control
Augmented reality for education and training
Intelligent transportation systems for traffic management
Predictive modeling for financial markets
Cloud computing for scalable data storage and processing
Virtual reality for therapy and mental health treatment
Data visualization for business intelligence
Recommender systems for personalized product recommendations
Speech recognition for voice-controlled devices
Mobile computing for real-time location-based services
Neural networks for predicting user behavior
Genetic algorithms for optimization problems
Distributed computing for parallel processing
Internet of things (IoT) for smart cities
Wireless sensor networks for environmental monitoring
Cloud-based gaming for high-performance gaming
Social network analysis for identifying influencers
Autonomous systems for agriculture
Robotics for disaster response
Data mining for customer segmentation
Computer graphics for visual effects in movies and video games
Virtual assistants for personalized customer service
Natural language understanding for chatbots
3D printing for manufacturing prototypes
Artificial intelligence for stock trading
Machine learning for weather forecasting
Biomedical engineering for prosthetics and implants
Cybersecurity for financial institutions
Machine learning for energy consumption optimization
Computer vision for object tracking
Natural language processing for document summarization
Wearable technology for health and fitness monitoring
Internet of things (IoT) for home automation
Reinforcement learning for robotics control
Big data analytics for customer insights
Machine learning for supply chain optimization
Natural language processing for legal document analysis
Artificial intelligence for drug discovery
Computer vision for object recognition in robotics
Data mining for customer churn prediction
Autonomous systems for space exploration
Robotics for agriculture automation
Machine learning for predicting earthquakes
Natural language processing for sentiment analysis in customer reviews
Big data analytics for predicting natural disasters
Internet of things (IoT) for remote patient monitoring
Blockchain technology for digital identity management
Machine learning for predicting wildfire spread
Computer vision for gesture recognition
Natural language processing for automated translation
Big data analytics for fraud detection in banking
Internet of things (IoT) for smart homes
Robotics for warehouse automation
Machine learning for predicting air pollution
Natural language processing for medical record analysis
Augmented reality for architectural design
Big data analytics for predicting traffic congestion
Machine learning for predicting customer lifetime value
Developing algorithms for efficient and accurate text recognition
Natural Language Processing for Virtual Assistants
Natural Language Processing for Sentiment Analysis in Social Media
Explainable Artificial Intelligence (XAI) for Trust and Transparency
Deep Learning for Image and Video Retrieval
Edge Computing for Internet of Things (IoT) Applications
Data Science for Social Media Analytics
Cybersecurity for Critical Infrastructure Protection
Natural Language Processing for Text Classification
Quantum Computing for Optimization Problems
Machine Learning for Personalized Health Monitoring
Computer Vision for Autonomous Driving
Blockchain Technology for Supply Chain Management
Augmented Reality for Education and Training
Natural Language Processing for Sentiment Analysis
Machine Learning for Personalized Marketing
Big Data Analytics for Financial Fraud Detection
Cybersecurity for Cloud Security Assessment
Artificial Intelligence for Natural Language Understanding
Blockchain Technology for Decentralized Applications
Virtual Reality for Cultural Heritage Preservation
Natural Language Processing for Named Entity Recognition
Machine Learning for Customer Churn Prediction
Big Data Analytics for Social Network Analysis
Cybersecurity for Intrusion Detection and Prevention
Artificial Intelligence for Robotics and Automation
Blockchain Technology for Digital Identity Management
Virtual Reality for Rehabilitation and Therapy
Natural Language Processing for Text Summarization
Machine Learning for Credit Risk Assessment
Big Data Analytics for Fraud Detection in Healthcare
Cybersecurity for Internet Privacy Protection
Artificial Intelligence for Game Design and Development
Blockchain Technology for Decentralized Social Networks
Virtual Reality for Marketing and Advertising
Natural Language Processing for Opinion Mining
Machine Learning for Anomaly Detection
Big Data Analytics for Predictive Maintenance in Transportation
Cybersecurity for Network Security Management
Artificial Intelligence for Personalized News and Content Delivery
Blockchain Technology for Cryptocurrency Mining
Virtual Reality for Architectural Design and Visualization
Natural Language Processing for Machine Translation
Machine Learning for Automated Image Captioning
Big Data Analytics for Stock Market Prediction
Cybersecurity for Biometric Authentication Systems
Artificial Intelligence for Human-Robot Interaction
Blockchain Technology for Smart Grids
Virtual Reality for Sports Training and Simulation
Natural Language Processing for Question Answering Systems
Machine Learning for Sentiment Analysis in Customer Feedback
Big Data Analytics for Predictive Maintenance in Manufacturing
Cybersecurity for Cloud-Based Systems
Artificial Intelligence for Automated Journalism
Blockchain Technology for Intellectual Property Management
Virtual Reality for Therapy and Rehabilitation
Natural Language Processing for Language Generation
Machine Learning for Customer Lifetime Value Prediction
Big Data Analytics for Predictive Maintenance in Energy Systems
Cybersecurity for Secure Mobile Communication
Artificial Intelligence for Emotion Recognition
Blockchain Technology for Digital Asset Trading
Virtual Reality for Automotive Design and Visualization
Natural Language Processing for Semantic Web
Machine Learning for Fraud Detection in Financial Transactions
Big Data Analytics for Social Media Monitoring
Cybersecurity for Cloud Storage and Sharing
Artificial Intelligence for Personalized Education
Blockchain Technology for Secure Online Voting Systems
Virtual Reality for Cultural Tourism
Natural Language Processing for Chatbot Communication
Machine Learning for Medical Diagnosis and Treatment
Big Data Analytics for Environmental Monitoring and Management.
Cybersecurity for Cloud Computing Environments
Virtual Reality for Training and Simulation
Big Data Analytics for Sports Performance Analysis
Cybersecurity for Internet of Things (IoT) Devices
Artificial Intelligence for Traffic Management and Control
Blockchain Technology for Smart Contracts
Natural Language Processing for Document Summarization
Machine Learning for Image and Video Recognition
Blockchain Technology for Digital Asset Management
Virtual Reality for Entertainment and Gaming
Natural Language Processing for Opinion Mining in Online Reviews
Machine Learning for Customer Relationship Management
Big Data Analytics for Environmental Monitoring and Management
Cybersecurity for Network Traffic Analysis and Monitoring
Artificial Intelligence for Natural Language Generation
Blockchain Technology for Supply Chain Transparency and Traceability
Virtual Reality for Design and Visualization
Natural Language Processing for Speech Recognition
Machine Learning for Recommendation Systems
Big Data Analytics for Customer Segmentation and Targeting
Cybersecurity for Biometric Authentication
Artificial Intelligence for Human-Computer Interaction
Blockchain Technology for Decentralized Finance (DeFi)
Virtual Reality for Tourism and Cultural Heritage
Machine Learning for Cybersecurity Threat Detection and Prevention
Big Data Analytics for Healthcare Cost Reduction
Cybersecurity for Data Privacy and Protection
Artificial Intelligence for Autonomous Vehicles
Blockchain Technology for Cryptocurrency and Blockchain Security
Virtual Reality for Real Estate Visualization
Natural Language Processing for Question Answering
Big Data Analytics for Financial Markets Prediction
Cybersecurity for Cloud-Based Machine Learning Systems
Artificial Intelligence for Personalized Advertising
Blockchain Technology for Digital Identity Verification
Virtual Reality for Cultural and Language Learning
Natural Language Processing for Semantic Analysis
Machine Learning for Business Forecasting
Big Data Analytics for Social Media Marketing
Artificial Intelligence for Content Generation
Blockchain Technology for Smart Cities
Virtual Reality for Historical Reconstruction
Natural Language Processing for Knowledge Graph Construction
Machine Learning for Speech Synthesis
Big Data Analytics for Traffic Optimization
Artificial Intelligence for Social Robotics
Blockchain Technology for Healthcare Data Management
Virtual Reality for Disaster Preparedness and Response
Natural Language Processing for Multilingual Communication
Machine Learning for Emotion Recognition
Big Data Analytics for Human Resources Management
Cybersecurity for Mobile App Security
Artificial Intelligence for Financial Planning and Investment
Blockchain Technology for Energy Management
Virtual Reality for Cultural Preservation and Heritage.
Big Data Analytics for Healthcare Management
Cybersecurity in the Internet of Things (IoT)
Artificial Intelligence for Predictive Maintenance
Computational Biology for Drug Discovery
Virtual Reality for Mental Health Treatment
Machine Learning for Sentiment Analysis in Social Media
Human-Computer Interaction for User Experience Design
Cloud Computing for Disaster Recovery
Quantum Computing for Cryptography
Intelligent Transportation Systems for Smart Cities
Cybersecurity for Autonomous Vehicles
Artificial Intelligence for Fraud Detection in Financial Systems
Social Network Analysis for Marketing Campaigns
Cloud Computing for Video Game Streaming
Machine Learning for Speech Recognition
Augmented Reality for Architecture and Design
Natural Language Processing for Customer Service Chatbots
Machine Learning for Climate Change Prediction
Big Data Analytics for Social Sciences
Artificial Intelligence for Energy Management
Virtual Reality for Tourism and Travel
Cybersecurity for Smart Grids
Machine Learning for Image Recognition
Augmented Reality for Sports Training
Natural Language Processing for Content Creation
Cloud Computing for High-Performance Computing
Artificial Intelligence for Personalized Medicine
Virtual Reality for Architecture and Design
Augmented Reality for Product Visualization
Natural Language Processing for Language Translation
Cybersecurity for Cloud Computing
Artificial Intelligence for Supply Chain Optimization
Blockchain Technology for Digital Voting Systems
Virtual Reality for Job Training
Augmented Reality for Retail Shopping
Natural Language Processing for Sentiment Analysis in Customer Feedback
Cloud Computing for Mobile Application Development
Artificial Intelligence for Cybersecurity Threat Detection
Blockchain Technology for Intellectual Property Protection
Virtual Reality for Music Education
Machine Learning for Financial Forecasting
Augmented Reality for Medical Education
Natural Language Processing for News Summarization
Cybersecurity for Healthcare Data Protection
Artificial Intelligence for Autonomous Robots
Virtual Reality for Fitness and Health
Machine Learning for Natural Language Understanding
Augmented Reality for Museum Exhibits
Natural Language Processing for Chatbot Personality Development
Cloud Computing for Website Performance Optimization
Artificial Intelligence for E-commerce Recommendation Systems
Blockchain Technology for Supply Chain Traceability
Virtual Reality for Military Training
Augmented Reality for Advertising
Natural Language Processing for Chatbot Conversation Management
Cybersecurity for Cloud-Based Services
Artificial Intelligence for Agricultural Management
Blockchain Technology for Food Safety Assurance
Virtual Reality for Historical Reenactments
Machine Learning for Cybersecurity Incident Response.
Secure Multiparty Computation
Federated Learning
Internet of Things Security
Blockchain Scalability
Quantum Computing Algorithms
Explainable AI
Data Privacy in the Age of Big Data
Adversarial Machine Learning
Deep Reinforcement Learning
Online Learning and Streaming Algorithms
Graph Neural Networks
Automated Debugging and Fault Localization
Mobile Application Development
Software Engineering for Cloud Computing
Cryptocurrency Security
Edge Computing for Real-Time Applications
Natural Language Generation
Virtual and Augmented Reality
Computational Biology and Bioinformatics
Internet of Things Applications
Robotics and Autonomous Systems
Explainable Robotics
3D Printing and Additive Manufacturing
Distributed Systems
Parallel Computing
Data Center Networking
Data Mining and Knowledge Discovery
Information Retrieval and Search Engines
Network Security and Privacy
Cloud Computing Security
Data Analytics for Business Intelligence
Neural Networks and Deep Learning
Reinforcement Learning for Robotics
Automated Planning and Scheduling
Evolutionary Computation and Genetic Algorithms
Formal Methods for Software Engineering
Computational Complexity Theory
Bio-inspired Computing
Computer Vision for Object Recognition
Automated Reasoning and Theorem Proving
Natural Language Understanding
Machine Learning for Healthcare
Scalable Distributed Systems
Sensor Networks and Internet of Things
Smart Grids and Energy Systems
Software Testing and Verification
Web Application Security
Wireless and Mobile Networks
Computer Architecture and Hardware Design
Digital Signal Processing
Game Theory and Mechanism Design
Multi-agent Systems
Evolutionary Robotics
Quantum Machine Learning
Computational Social Science
Explainable Recommender Systems.
Artificial Intelligence and its applications
Cloud computing and its benefits
Cybersecurity threats and solutions
Internet of Things and its impact on society
Virtual and Augmented Reality and its uses
Blockchain Technology and its potential in various industries
Web Development and Design
Digital Marketing and its effectiveness
Big Data and Analytics
Software Development Life Cycle
Gaming Development and its growth
Network Administration and Maintenance
Machine Learning and its uses
Data Warehousing and Mining
Computer Architecture and Design
Computer Graphics and Animation
Quantum Computing and its potential
Data Structures and Algorithms
Computer Vision and Image Processing
Robotics and its applications
Operating Systems and its functions
Information Theory and Coding
Compiler Design and Optimization
Computer Forensics and Cyber Crime Investigation
Distributed Computing and its significance
Artificial Neural Networks and Deep Learning
Cloud Storage and Backup
Programming Languages and their significance
Computer Simulation and Modeling
Computer Networks and its types
Information Security and its types
Computer-based Training and eLearning
Medical Imaging and its uses
Social Media Analysis and its applications
Human Resource Information Systems
Computer-Aided Design and Manufacturing
Multimedia Systems and Applications
Geographic Information Systems and its uses
Computer-Assisted Language Learning
Mobile Device Management and Security
Data Compression and its types
Knowledge Management Systems
Text Mining and its uses
Cyber Warfare and its consequences
Wireless Networks and its advantages
Computer Ethics and its importance
Computational Linguistics and its applications
Autonomous Systems and Robotics
Information Visualization and its importance
Geographic Information Retrieval and Mapping
Business Intelligence and its benefits
Digital Libraries and their significance
Artificial Life and Evolutionary Computation
Computer Music and its types
Virtual Teams and Collaboration
Computer Games and Learning
Semantic Web and its applications
Electronic Commerce and its advantages
Multimedia Databases and their significance
Computer Science Education and its importance
Computer-Assisted Translation and Interpretation
Ambient Intelligence and Smart Homes
Autonomous Agents and Multi-Agent Systems.

About the author

Muhammad Hassan

Researcher, Academic Writer, Web developer

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The Top 10 Most Interesting Computer Science Research Topics

Computer science touches nearly every area of our lives. With new advancements in technology, the computer science field is constantly evolving, giving rise to new computer science research topics. These topics attempt to answer various computer science research questions and how they affect the tech industry and the larger world.

Computer science research topics can be divided into several categories, such as artificial intelligence, big data and data science, human-computer interaction, security and privacy, and software engineering. If you are a student or researcher looking for computer research paper topics. In that case, this article provides some suggestions on examples of computer science research topics and questions.

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What makes a strong computer science research topic.

A strong computer science topic is clear, well-defined, and easy to understand. It should also reflect the research’s purpose, scope, or aim. In addition, a strong computer science research topic is devoid of abbreviations that are not generally known, though, it can include industry terms that are currently and generally accepted.

Tips for Choosing a Computer Science Research Topic

Brainstorm . Brainstorming helps you develop a few different ideas and find the best topic for you. Some core questions you should ask are, What are some open questions in computer science? What do you want to learn more about? What are some current trends in computer science?
Choose a sub-field . There are many subfields and career paths in computer science . Before choosing a research topic, ensure that you point out which aspect of computer science the research will focus on. That could be theoretical computer science, contemporary computing culture, or even distributed computing research topics.
Aim to answer a question . When you’re choosing a research topic in computer science, you should always have a question in mind that you’d like to answer. That helps you narrow down your research aim to meet specified clear goals.
Do a comprehensive literature review . When starting a research project, it is essential to have a clear idea of the topic you plan to study. That involves doing a comprehensive literature review to better understand what has been learned about your topic in the past.
Keep the topic simple and clear. The topic should reflect the scope and aim of the research it addresses. It should also be concise and free of ambiguous words. Hence, some researchers recommended that the topic be limited to five to 15 substantive words. It can take the form of a question or a declarative statement.

What’s the Difference Between a Research Topic and a Research Question?

A research topic is the subject matter that a researcher chooses to investigate. You may also refer to it as the title of a research paper. It summarizes the scope of the research and captures the researcher’s approach to the research question. Hence, it may be broad or more specific. For example, a broad topic may read, Data Protection and Blockchain, while a more specific variant can read, Potential Strategies to Privacy Issues on the Blockchain.

On the other hand, a research question is the fundamental starting point for any research project. It typically reflects various real-world problems and, sometimes, theoretical computer science challenges. As such, it must be clear, concise, and answerable.

How to Create Strong Computer Science Research Questions

To create substantial computer science research questions, one must first understand the topic at hand. Furthermore, the research question should generate new knowledge and contribute to the advancement of the field. It could be something that has not been answered before or is only partially answered. It is also essential to consider the feasibility of answering the question.

2. The Influence of Extraction Methods on Big Data Mining

Data mining has drawn the scientific community’s attention, especially with the explosive rise of big data. Many research results prove that the extraction methods used have a significant effect on the outcome of the data mining process. However, a topic like this analyzes algorithms. It suggests strategies and efficient algorithms that may help understand the challenge or lead the way to find a solution.

3. Integration of 5G with Analytics and Artificial Intelligence

According to the International Finance Corporation, 5G and AI technologies are defining emerging markets and our world. Through different technologies, this research aims to find novel ways to integrate these powerful tools to produce excellent results. Subjects like this often spark great discoveries that pioneer new levels of research and innovation. A breakthrough can influence advanced educational technology, virtual reality, metaverse, and medical imaging.

4. Leveraging Asynchronous FPGAs for Crypto Acceleration

To support the growing cryptocurrency industry, there is a need to create new ways to accelerate transaction processing. This project aims to use asynchronous Field-Programmable Gate Arrays (FPGAs) to accelerate cryptocurrency transaction processing. It explores how various distributed computing technologies can influence mining cryptocurrencies faster with FPGAs and generally enjoy faster transactions.

5. Cyber Security Future Technologies

Cyber security is a trending topic among businesses and individuals, especially as many work teams are going remote. Research like this can stretch the length and breadth of the cyber security and cloud security industries and project innovations depending on the researcher’s preferences. Another angle is to analyze existing or emerging solutions and present discoveries that can aid future research.

6. Exploring the Boundaries Between Art, Media, and Information Technology

The field of computers and media is a vast and complex one that intersects in many ways. They create images or animations using design technology like algorithmic mechanism design, design thinking, design theory, digital fabrication systems, and electronic design automation. This paper aims to define how both fields exist independently and symbiotically.

7. Evolution of Future Wireless Networks Using Cognitive Radio Networks

This research project aims to study how cognitive radio technology can drive evolution in future wireless networks. It will analyze the performance of cognitive radio-based wireless networks in different scenarios and measure its impact on spectral efficiency and network capacity. The research project will involve the development of a simulation model for studying the performance of cognitive radios in different scenarios.

8. The Role of Quantum Computing and Machine Learning in Advancing Medical Predictive Systems

In a paper titled Exploring Quantum Computing Use Cases for Healthcare , experts at IBM highlighted precision medicine and diagnostics to benefit from quantum computing. Using biomedical imaging, machine learning, computational biology, and data-intensive computing systems, researchers can create more accurate disease progression prediction, disease severity classification systems, and 3D Image reconstruction systems vital for treating chronic diseases.

9. Implementing Privacy and Security in Wireless Networks

Wireless networks are prone to attacks, and that has been a big concern for both individual users and organizations. According to the Cyber Security and Infrastructure Security Agency CISA, cyber security specialists are working to find reliable methods of securing wireless networks . This research aims to develop a secure and privacy-preserving communication framework for wireless communication and social networks.

10. Exploring the Challenges and Potentials of Biometric Systems Using Computational Techniques

Much discussion surrounds biometric systems and the potential for misuse and privacy concerns. When exploring how biometric systems can be effectively used, issues such as verification time and cost, hygiene, data bias, and cultural acceptance must be weighed. The paper may take a critical study into the various challenges using computational tools and predict possible solutions.

Computer Research Questions

Why are there so many programming languages?
Is there a better way to enhance human-computer interactions in computer-aided learning?
How safe is cloud computing, and what are some ways to enhance security?
Can computers effectively assist in the sequencing of human genes?
How valuable is SCRUM methodology in Agile software development?

Choosing the Right Computer Science Research Topic

Computer science research is a vast field, and it can be challenging to choose the right topic. There are a few things to keep in mind when making this decision. Choose a topic that you are interested in. This will make it easier to stay motivated and produce high-quality research for your computer science degree .

Select a topic that is relevant to your field of study. This will help you to develop specialized knowledge in the area. Choose a topic that has potential for future research. This will ensure that your research is relevant and up-to-date. Typically, coding bootcamps provide a framework that streamlines students’ projects to a specific field, doing their search for a creative solution more effortless.

Computer Science Research Topics FAQ

To start a computer science research project, you should look at what other content is out there. Complete a literature review to know the available findings surrounding your idea. Design your research and ensure that you have the necessary skills and resources to complete the project.

The first step to conducting computer science research is to conceptualize the idea and review existing knowledge about that subject. You will design your research and collect data through surveys or experiments. Analyze your data and build a prototype or graphical model. You will also write a report and present it to a recognized body for review and publication.

You can find computer science research jobs on the job boards of many universities. Many universities have job boards on their websites that list open positions in research and academia. Also, many Slack and GitHub channels for computer scientists provide regular updates on available projects.

There are several hot topics and questions in AI that you can build your research on. Below are some AI research questions you may consider for your research paper.

Will it be possible to build artificial emotional intelligence?
Will robots replace humans in all difficult cumbersome jobs as part of the progress of civilization?
Can artificial intelligence systems self-improve with knowledge from the Internet?

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EECS’ research covers a wide variety of topics in electrical engineering , computer science , and artificial intelligence and decision-making .

The future of our society is interwoven with the future of data-driven thinking—most prominently, artificial intelligence is set to reshape every aspect of our lives. Research in this area studies the interface between AI-driven systems and human actors, exploring both the impact of data-driven decision-making on human behavior and experience, and how AI technologies can be used to improve access to opportunities. This research combines a variety of areas including AI, machine learning, economics, social psychology, and law.

Our goal is to develop AI technologies that will change the landscape of healthcare. This includes early diagnostics, drug discovery, care personalization and management. Building on MIT’s pioneering history in artificial intelligence and life sciences, we are working on algorithms suitable for modeling biological and clinical data across a range of modalities including imaging, text and genomics.

Our research covers a wide range of topics of this fast-evolving field, advancing how machines learn, predict, and control, while also making them secure, robust and trustworthy. Research covers both the theory and applications of ML. This broad area studies ML theory (algorithms, optimization, …), statistical learning (inference, graphical models, causal analysis, …), deep learning, reinforcement learning, symbolic reasoning ML systems, as well as diverse hardware implementations of ML.

We develop the technology and systems that will transform the future of biology and healthcare. Specific areas include biomedical sensors and electronics, nano- and micro-technologies, imaging, and computational modeling of disease.

We develop the next generation of wired and wireless communications systems, from new physical principles (e.g., light, terahertz waves) to coding and information theory, and everything in between.

We bring some of the most powerful tools in computation to bear on design problems, including modeling, simulation, processing and fabrication.

We design the next generation of computer systems. Working at the intersection of hardware and software, our research studies how to best implement computation in the physical world. We design processors that are faster, more efficient, easier to program, and secure. Our research covers systems of all scales, from tiny Internet-of-Things devices with ultra-low-power consumption to high-performance servers and datacenters that power planet-scale online services. We design both general-purpose processors and accelerators that are specialized to particular application domains, like machine learning and storage. We also design Electronic Design Automation (EDA) tools to facilitate the development of such systems.

Educational technology combines both hardware and software to enact global change, making education accessible in unprecedented ways to new audiences. We develop the technology that makes better understanding possible.

Our research spans a wide range of materials that form the next generation of devices, and includes groundbreaking research on graphene & 2D materials, quantum computing, MEMS & NEMS, and new substrates for computation.

Our research focuses on solving challenges related to the transduction, transmission, and control of energy and energy systems. We develop new materials for energy storage, devices and power electronics for harvesting, generation and processing of energy, and control of large-scale energy systems.

The shared mission of Visual Computing is to connect images and computation, spanning topics such as image and video generation and analysis, photography, human perception, touch, applied geometry, and more.

The focus of our research in Human-Computer Interaction (HCI) is inventing new systems and technology that lie at the interface between people and computation, and understanding their design, implementation, and societal impact.

This broad research theme covered activities across all aspects of systems that process information, and the underlying science and mathematics, and includes communications, networking & information theory; numerical and computational simulation and prototyping; signal processing and inference; medical imaging; data science, statistics and inference.

Our field deals with the design and creation of sophisticated circuits and systems for applications ranging from computation to sensing.

Our research focuses on the creation of materials and devices at the nano scale to create novel systems across a wide variety of application areas.

Our research encompasses all aspects of speech and language processing—ranging from the design of fundamental machine learning methods to the design of advanced applications that can extract information from documents, translate between languages, and execute instructions in real-world environments.

Our work focuses on materials, devices, and systems for optical and photonic applications, with applications in communications and sensing, femtosecond optics, laser technologies, photonic bandgap fibers and devices, laser medicine and medical imaging, and millimeter-wave and terahertz devices.

Research in this area focuses on developing efficient and scalable algorithms for solving large scale optimization problems in engineering, data science and machine learning. Our work also studies optimal decision making in networked settings, including communication networks, energy systems and social networks. The multi-agent nature of many of these systems also has led to several research activities that rely on game-theoretic approaches.

We develop new approaches to programming, whether that takes the form of programming languages, tools, or methodologies to improve many aspects of applications and systems infrastructure.

Our work focuses on developing the next substrate of computing, communication and sensing. We work all the way from new materials to superconducting devices to quantum computers to theory.

Our research focuses on robotic hardware and algorithms, from sensing to control to perception to manipulation.

Our research is focused on making future computer systems more secure. We bring together a broad spectrum of cross-cutting techniques for security, from theoretical cryptography and programming-language ideas, to low-level hardware and operating-systems security, to overall system designs and empirical bug-finding. We apply these techniques to a wide range of application domains, such as blockchains, cloud systems, Internet privacy, machine learning, and IoT devices, reflecting the growing importance of security in many contexts.

Signal processing focuses on algorithms and hardware for analyzing, modifying and synthesizing signals and data, across a wide variety of application domains. As a technology it plays a key role in virtually every aspect of modern life including for example entertainment, communications, travel, health, defense and finance.

From distributed systems and databases to wireless, the research conducted by the systems and networking group aims to improve the performance, robustness, and ease of management of networks and computing systems.

Our theoretical research includes quantification of fundamental capabilities and limitations of feedback systems, inference and control over networks, and development of practical methods and algorithms for decision making under uncertainty.

Theory of Computation (TOC) studies the fundamental strengths and limits of computation, how these strengths and limits interact with computer science and mathematics, and how they manifest themselves in society, biology, and the physical world.

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Computer science articles from across Nature Portfolio

Computer science is the study and development of the protocols required for automated processing and manipulation of data. This includes, for example, creating algorithms for efficiently searching large volumes of information or encrypting data so that it can be stored and transmitted securely.

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7 Important Computer Science Trends 2024-2027

1. Quantum computing makes waves

Quantum computing is the use of quantum mechanics, such as entanglement and superposition, to perform computations.

It uses quantum bits ( qubits ) in a similar way that regular computers use bits.

Quantum computers have the potential to solve problems that would take the world's most powerful supercomputers millions of years .

Companies including IBM, Microsoft and Google are all in competition to build reliable quantum computers.

In fact, In September 2019, Google AI and NASA published a joint paper that claimed to have achieved "quantum supremacy".

This is when a quantum computer outperforms a traditional one at a particular task.

Quantum computers have the potential to completely transform data science.

They also have the potential to accelerate the development of artificial intelligence, virtual reality, big data, deep learning, encryption, medicine and more.

The downside is that quantum computers are currently incredibly difficult to build and sensitive to interference.

Despite current limitations, it's fair to expect further advances from Google and others that will help make quantum computers practical to use.

Which would position quantum computing as one of the most important computer science trends in the coming years.

2. Zero Trust becomes the norm

Most information security frameworks used by organizations use traditional trust authentication methods (like passwords).

These frameworks focus on protecting network access.

And they assume that anyone that has access to the network should be able to access any data and resources they'd like.

There's a big downside to this approach: a bad actor who has got in via any entry point can then move around freely to access all data or delete it altogether.

Zero Trust information security models aim to prevent this potential vulnerability.

Zero Trust models replace the old assumption that every user within an organization’s network can be trusted.

Instead, nobody is trusted, whether they’re already inside or outside the network.

Verification is required from everyone trying to gain access to any resource on the network.

Huge companies like Cisco are investing heavily to develop Zero Trust solutions.

This security architecture is quickly moving from just a computer science concept to industry best practice.

And it’s little wonder why: IBM reports that the average data breach costs a company $3.86 million in damages .

And that it takes an average of 280 days to fully recover.

We will see demand for this technology continue to skyrocket in 2024 and beyond as businesses adopt zero-trust security to mitigate this risk.

3. Cloud computing hits the edge

“ Edge computing ” searches have risen 161% over the past 5 years. This market may be worth $8.67 billion by 2025.

Gartner estimates that 80% of enterprises will shut down their traditional data centers by 2025.

This is mainly because traditional cloud computing relies on servers in one central location.

If the end-user is in another country, they have to wait while data travels thousands of miles.

Latency issues like this can really hamper an application’s performance (especially for high-bandwidth media, like video).

Which is why many companies are moving over to edge computing service providers instead.

Modern edge computing brings computation, data storage, and data analytics as close as possible to the end-user location.

And when edge servers host web applications the result is massively improved response times.

As a result, some estimates suggest that the edge computing market will be worth $61.14 billion by 2028.

And Content Delivery Networks like Cloudflare that make edge computing easy and accessible will increasingly power the web.

4. Kotlin overtakes Java

“ Kotlin ” searches are up 95% in 5 years. Interest in this programming language rocketed in 2022.

Kotlin is a general-purpose programming language that first appeared in 2011.

It’s designed specifically to be a more concise and streamlined version of Java.

And so it works for both JVM (Java Virtual Machine) and Android development.

Kotlin is billed as a modern programming language that makes developers happier.

There are over 7 million Java programmers in the world right now.

Since Kotlin offers big advantages over Java, we can expect more and more programmers to make the switch between 2023 and 2026.

Google even made the announcement in 2019 that Kotlin is now its preferred language for Android app developers.

5. The web becomes more standardized

REST (Representational State Transfer) web services power the internet and the data behind it.

But the structure of each REST API data source varies wildly.

It depends entirely on how the individual programmer behind it decided to design it.

The OpenAPI Specification (OAS) changes this. It’s essentially a description format for REST APIs.

Data sources that implement OAS are easy to learn and readable to both humans and machines.

This is because an OpenAPI file describes the entire API, including available endpoints, operations and outputs.

This standardization enables the automation of previously time-consuming tasks.

For example, tools like Swagger generate code, documentation and test cases given the OAS interface file.

This can save a huge amount of engineering time both upfront and in the long run.

Another technology that takes this concept to the next level is GraphQL . This is a data query language for APIs developed at Facebook .

It provides a complete description of the data available in a particular source. And it also gives clients the ability to ask for only the specific parts of the data they need and nothing more.

GraphQL is a query language for APIs and a runtime for fulfilling those queries with your existing data.

It too has become widely used and massively popular. Frameworks and specifications like this that standardize all aspects of the internet will continue to gain wide adoption.

6. More digital twins

Interest in “ Digital twin ” has steadily grown (300%) over the last 5 years.

A digital twin is a software representation of a real-world entity or process, from which you can generate and analyze simulation data.

This way you can improve efficiency and avoid problems before devices are even built and deployed.

GE is the big name in the field and has developed internal digital twin technology to improve its own jet-engine manufacturing process.

GE's Predix platform is a huge player in the digital twin technology market.

This technology was initially only available at the big enterprise level, with GE’s Predix industrial Internet of Things (IoT) platform.

But now we’re seeing its usage permeate across other sectors like retail warehousing, auto manufacturing, and healthcare planning.

Yet case studies of these real-world use cases are thin on the ground, so the people who produce them will set themselves up as industry experts in their field.

7. Demand for cybersecurity expertise skyrockets

“ Hack The Box ” searches have increased by 285% over 5 years.

According to CNET, at least 7.9 billion records (including credit card numbers, home addresses and phone numbers) were exposed through data breaches in 2019 alone.

As a consequence, large numbers of companies seek cybersecurity expertise to protect themselves.

Hack The Box is an online platform that has a wealth of educational information and hundreds of cybersecurity-themed challenges.

And they have 290,000 active users that test and improve their skills in penetration testing.

So they’ve become the go-to place for companies to recruit new talent for their cybersecurity teams.

Hack The Box is a hacker haven both in terms of content and design.

And software that helps people to identify if they’ve had their credentials compromised by data breaches will also trend.

One of the most well-known tools currently is Have I Been Pwned .

It allows you to search across multiple data breaches to see if your email address has been compromised.

That's our list of the 7 most important computer science trends to keep an eye on over the next 3-4 years.

From machine learning to blockchain to AR, it's an exciting time to be in the computer science field.

CS has always been a rapidly changing industry.

But with the growth of completely new technologies (especially cloud computing and machine learning), it's fair to expect that the rate of change will increase in 2024 and beyond.

Find Thousands of Trending Topics With Our Platform

What Are the Latest Trends in Computer Science and Technology?

Holland Webb

Contributing Writer

Learn about our editorial process .

Updated April 30, 2024

Mitch Jacobson

Contributing Editor

Reviewed by

Monali Mirel Chuatico

Contributing Reviewer

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Are you ready to discover your college program?

Computer science is among the most future-proof career fields — it's always changing and becomes more enmeshed in our lives every day. The latest computer technology can learn to adjust its actions to suit its environment, help carry out a complex surgery, map an organism's genome, or drive a car.

A complex web of industry needs, national security interests, healthcare opportunities, supply chain fragility, and user demand drive these trends. Technology developers and engineers are building the tools that may solve the climate crisis, make exceptional healthcare accessible to rural residents, or optimize the global supply chain.

If you plan to serve in computer science, you need to stay abreast of the trends — or risk falling behind.

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Learn about start dates, transferring credits, availability of financial aid, and more by contacting the universities below.

Top Computer Science Trends

Generative AI

Generative artificial intelligence (AI) is a type of artificial intelligence that can create new content, such as articles, images, and videos. Anyone who has used ChatGPT or Microsoft Copilot has toyed with generative AI. These AI models can summarize and classify information or answer questions because they have been trained to recognize patterns in data.

The research firm McKinsey & Company predicts that in the coming years, generative AI could contribute $4.4 trillion to the economy annually. Despite its obvious business advantages, many AI tools create content that sounds convincing and authoritative but is riddled with inaccuracies. Using this content can put companies at risk of regulatory penalties or consumer pushback.

Still, machine learning engineers, data scientists , and chatbot developers strive to make AI better and more accessible.

Job Outlook: The U.S. Bureau of Labor Statistics (BLS) projects that computer and information research scientist jobs, a broad career category that includes AI researchers, will grow 23% from 2022 to 2032. These workers earned a median wage of $145,080 in 2023. According to Payscale , as of April 2024, machine learning engineers make an average annual salary of $118,350.

Potential Careers:

Computer Researcher
Machine Learning Engineer
Senior Data Scientist
Robotics Engineer
Algorithm Engineer

Education Required: Entry-level artificial intelligence jobs may require a bachelor's degree, but engineers, researchers, and data scientists often need a master's degree or a doctorate.

Quantum Computing

Quantum computing operates on subatomic particles rather than a stream of binary impulses, and its bits, called qubits, can exist in more than one state simultaneously. It is much more powerful, but far less well-developed, than traditional computing. Should quantum computing become widely accessible, it would challenge current communication and cryptography practices.

Only a few quantum computing devices exist, and these are highly specialized. Although the concept of quantum computing has generated a lot of buzz, some experts wonder if the concept is truly viable, and whether the benefits outweigh the costs.

Nevertheless, organizations like the Central Intelligence Agency and tech companies like IBM are hiring quantum computing specialists. Many of these jobs call for a master's degree in a technical field like physics, mathematics, or electrical engineering.

Job Outlook: ZipRecruiter reports quantum computing professionals earn an average annual salary of $131,240 as of March 2024. Since quantum computing is still a relatively niche field, reliable job growth data is unavailable.

Quantum Machine Learning Scientist
Quantum Software Developer
Quantum Algorithm Researcher
Quantum Control Researcher
Qubit Researcher

Education Required: Quantum computing careers usually require a graduate degree.

Bioinformatics

Bioinformatics combines biology with computer science and generally focuses on data collection and analysis. Biologists use bioinformatics to spot patterns in their data. For example, a scientist can use bioinformatics tools and techniques to help sequence organisms' genomes.

As knowledge of biology expands, so does interest in bioinformatics. For example, research from BDO , a professional services firm, indicates spending on research and development in biotech grew nearly 22% from 2018 to 2019. Bioinformatics companies include Helix, Seven Bridges, and Thermo Fisher Scientific.

Bioinformatics specialists should have skills in cluster analysis, algorithm development, server cluster management, and protein sequencing analysis. Careers in this industry include biostatistician, bioinformatician, and bioinformatics scientist.

Job Outlook: The BLS projects that bioengineer and biomedical engineer jobs will grow 5% from 2022 to 2032. These workers earned a median wage of $100,730 in 2023.

Bioinformatics Research Scientist
Bioinformatics Engineer
Biomedical Researcher
Biostatistician
Computational Biologist

Education Required: Most bioinformatics careers require a bachelor's degree or higher. Leadership, research, and teaching positions may require a master's degree or Ph.D.

Remote Healthcare

Remote healthcare lets medical providers use technology to monitor the health of patients who cannot travel to providers' offices. Supporters of this field say remote healthcare improves patient outcomes while reducing costs.

EMARKETER produced a 2021 report that projects 70.6 million people will use remote patient monitoring devices by 2025, up from 29.1 million in 2020. The rising prevalence of chronic conditions, an aging patient population, and the need for cost-effective medical services are all helping drive this trend.

Physicians, therapists, and advanced practice professionals can use remote patient monitoring, but affordability, patient behaviors, and lack of awareness threaten widespread adoption. Companies in this field include GYANT, Medopad, and Cardiomo.

Job Outlook: The BLS projects that the healthcare field will have 1.8 million annual openings from 2022 to 2032. Healthcare practitioners and technical workers earned a median wage of $80,820 in 2023.

Physician Assistant
Nurse Practitioner
Registered Nurse
Healthcare Business Analyst
Health Tech Software Engineer
Licensed Professional Counselor

Education Required: Doctors need an MD or DO, advanced practice professionals and counselors must hold a master's degree, and registered nurses need at least an associate degree. All medical providers must also hold licensure.

Cybersecurity

Cybersecurity is an umbrella term that refers to protecting digital assets from cyberthreats. Most attacks are coordinated efforts to access or change information, extort money, or disrupt business.

In 2022, McKinsey & Associates projected the cost of cybersecurity attacks would grow to $10.5 trillion annually by 2025, increasing 300% from 2015. Sophisticated artificial intelligence tools drive an increase in deep fakes, hacking, and data breaches. Companies such as Cisco, IBM, and Palo Alto Networks are building novel cybersecurity technologies to combat these threats.

Jobs in the field include security engineer, cryptographer, and ethical hacker. These positions often pay lucrative salaries and require academic degrees and professional credentials, such as the CompTIA security+ certification. Cybersecurity is not generally an entry-level field , so most new practitioners have computer science experience.

Job Outlook: The BLS projects that information security analyst jobs will grow 32% from 2022 to 2032. These workers earned a median wage of $120,360 in 2023.

Information Security Analyst
Digital Forensic Examiner
Penetration Tester
Security Engineer

Education Required: Cybersecurity experts usually need a bachelor's degree and relevant professional certifications.

Autonomic, Autonomous, and Hybrid Systems

Autonomous may sound synonymous with autonomic, but the two words actually have different meanings. Autonomous machines operate with little or no human control — think of industrial robots or self-driving cars. Autonomic computing, in contrast, controls itself while also responding to its environment — think of the industrial Internet of Things and predictive AI.

This field has generated tremendous interest for its capacity to alter healthcare provision, transportation, supply chains, and anything that depends on smart technology. Companies like Tesla, Fetch Robotics, and Knightscope work in autonomic, autonomous, and hybrid systems, building everything from self-piloting security robots to intelligent machines that assist warehouse workers.

Autonomic, autonomous, and hybrid systems may lead to tremendous creative freedom for human beings. However, these subfields also present numerous ethical and moral questions, such as who is responsible for intelligent machines' bad decisions?

Job Outlook: The BLS projects that aerospace engineer jobs will grow 6% and mechanical engineer jobs will grow 10% from 2022 to 2032. In 2023, these professionals earned median wages of $130,720 and $99,510, respectively. According to Payscale data from April 2024, machine learning engineers make an average annual salary of $118,350.

Chief Engineer - Autonomous Systems Development
Autonomous Control Systems Design Engineer
Autonomy Engineer
Machine Learning Accelerator Architect
Silicon Emulation Engineer

Education Required: Engineers who build autonomous systems usually need a bachelor's degree and state licensure. Professionals who work in universities may need a Ph.D.

Regenerative Agritech

Regenerative agriculture takes a holistic approach to farming that aims to foster biodiversity, rebuild soil, and promote food security. Under this method, farmers seek to limit their greenhouse gas emissions, reduce synthetic fertilizers, and improve water usage.

These goals require technological tools that companies such as Trace Genomics, Future Fields, and ProducePay create. For example, Future Fields built a device to harness fruit flies and produce recombinant proteins sustainably.

While regenerative agriculture may become a powerful tool to help decarbonize the food system, reduce climate change, and improve crop resilience, it needs to scale three times faster than its current growth rate to maximize its benefits, according to a 2023 report from the European Commission. The field will require greater technological innovations to fulfill its potential.

Job Outlook: The BLS projects that agricultural engineer jobs will grow 6% from 2022 to 2032. These workers made a median wage of $88,750 in 2023.

Agritech Research Associate
Bioeconomy Consultant
Agricultural Digital and Technology Leader
Agritech Program Designer
Agricultural Engineer

Education Required: Agricultural engineers usually need a bachelor's degree. Program designers and research associates may need a graduate degree.

More Tech Trends on the Horizon

Digital trendsetters are working in industry, academia, government, and professional organizations to advance machine capabilities, safety, and accessibility. Consequently, some niche industries create new opportunities with nascent technologies.

For example, digital twin models can let scientists perform research more thoroughly to make products and processes safer. Similarly, low-power AI accelerators may allow autonomous vehicles or AI robots to perform their typical work when a power grid or battery is unavailable.

Other long-standing trends continue to advance: Blockchain , edge computing, cloud computing, and the Internet of Things are growing in capacity or user acceptance.

Human-computer interaction is also scaling up: As devices become wearable or implantable and the line between the virtual and physical worlds gets blurrier, existential questions about humanity, reality, and ethics are taking on greater significance.

How Robotics Can Help Future Tech Students

Blockchain Technology and the Future of Sustainability

Best Programming Languages to Learn

Frequently asked questions about trends in computer science, what's the next big thing in computer science.

Artificial intelligence is probably the most-discussed technology in the computer science universe right now. Future developments for AI include intersections with cryptography, virtual reality, and hyperdimensional vectors.

Do I need to go to school to learn computer science?

You do not have to learn computer science in a formal classroom, but attending school can help you acquire knowledge faster and launch your career more effectively. Consider a bootcamp, certificate, or micro-master's program if a full computer science degree isn't for you.

What new technologies in computer science should I learn?

New computer science technologies include innovations in artificial intelligence, data analytics, machine learning, virtual and augmented reality, UI/UX design, and quantum computing. You can also study fields like blockchain, edge computing, and the Internet of Things.

Which fields of computer science are in most demand?

The BLS projects that information security analyst, software developer, and computer and information research scientist jobs will each grow more than 20% between 2022 and 2032 — much faster than the national projected growth for all careers. In-demand computer science subfields include robotics, bioinformatics, machine learning, computer forensics, big data, and cloud computing.

Page last reviewed April 16, 2024.

Research Topics & Ideas: CompSci & IT

50+ Computer Science Research Topic Ideas To Fast-Track Your Project

Finding and choosing a strong research topic is the critical first step when it comes to crafting a high-quality dissertation, thesis or research project. If you’ve landed on this post, chances are you’re looking for a computer science-related research topic , but aren’t sure where to start. Here, we’ll explore a variety of CompSci & IT-related research ideas and topic thought-starters, including algorithms, AI, networking, database systems, UX, information security and software engineering.

NB – This is just the start…

The topic ideation and evaluation process has multiple steps . In this post, we’ll kickstart the process by sharing some research topic ideas within the CompSci domain. This is the starting point, but to develop a well-defined research topic, you’ll need to identify a clear and convincing research gap , along with a well-justified plan of action to fill that gap.

If you’re new to the oftentimes perplexing world of research, or if this is your first time undertaking a formal academic research project, be sure to check out our free dissertation mini-course. In it, we cover the process of writing a dissertation or thesis from start to end. Be sure to also sign up for our free webinar that explores how to find a high-quality research topic.

Overview: CompSci Research Topics

Algorithms & data structures
Artificial intelligence ( AI )
Computer networking
Database systems
Human-computer interaction
Information security (IS)
Software engineering
Examples of CompSci dissertation & theses

Topics/Ideas: Algorithms & Data Structures

An analysis of neural network algorithms’ accuracy for processing consumer purchase patterns
A systematic review of the impact of graph algorithms on data analysis and discovery in social media network analysis
An evaluation of machine learning algorithms used for recommender systems in streaming services
A review of approximation algorithm approaches for solving NP-hard problems
An analysis of parallel algorithms for high-performance computing of genomic data
The influence of data structures on optimal algorithm design and performance in Fintech
A Survey of algorithms applied in internet of things (IoT) systems in supply-chain management
A comparison of streaming algorithm performance for the detection of elephant flows
A systematic review and evaluation of machine learning algorithms used in facial pattern recognition
Exploring the performance of a decision tree-based approach for optimizing stock purchase decisions
Assessing the importance of complete and representative training datasets in Agricultural machine learning based decision making.
A Comparison of Deep learning algorithms performance for structured and unstructured datasets with “rare cases”
A systematic review of noise reduction best practices for machine learning algorithms in geoinformatics.
Exploring the feasibility of applying information theory to feature extraction in retail datasets.
Assessing the use case of neural network algorithms for image analysis in biodiversity assessment

Topics & Ideas: Artificial Intelligence (AI)

Applying deep learning algorithms for speech recognition in speech-impaired children
A review of the impact of artificial intelligence on decision-making processes in stock valuation
An evaluation of reinforcement learning algorithms used in the production of video games
An exploration of key developments in natural language processing and how they impacted the evolution of Chabots.
An analysis of the ethical and social implications of artificial intelligence-based automated marking
The influence of large-scale GIS datasets on artificial intelligence and machine learning developments
An examination of the use of artificial intelligence in orthopaedic surgery
The impact of explainable artificial intelligence (XAI) on transparency and trust in supply chain management
An evaluation of the role of artificial intelligence in financial forecasting and risk management in cryptocurrency
A meta-analysis of deep learning algorithm performance in predicting and cyber attacks in schools

Topics & Ideas: Networking

An analysis of the impact of 5G technology on internet penetration in rural Tanzania
Assessing the role of software-defined networking (SDN) in modern cloud-based computing
A critical analysis of network security and privacy concerns associated with Industry 4.0 investment in healthcare.
Exploring the influence of cloud computing on security risks in fintech.
An examination of the use of network function virtualization (NFV) in telecom networks in Southern America
Assessing the impact of edge computing on network architecture and design in IoT-based manufacturing
An evaluation of the challenges and opportunities in 6G wireless network adoption
The role of network congestion control algorithms in improving network performance on streaming platforms
An analysis of network coding-based approaches for data security
Assessing the impact of network topology on network performance and reliability in IoT-based workspaces

Free Webinar: How To Find A Dissertation Research Topic

Topics & Ideas: Database Systems

An analysis of big data management systems and technologies used in B2B marketing
The impact of NoSQL databases on data management and analysis in smart cities
An evaluation of the security and privacy concerns of cloud-based databases in financial organisations
Exploring the role of data warehousing and business intelligence in global consultancies
An analysis of the use of graph databases for data modelling and analysis in recommendation systems
The influence of the Internet of Things (IoT) on database design and management in the retail grocery industry
An examination of the challenges and opportunities of distributed databases in supply chain management
Assessing the impact of data compression algorithms on database performance and scalability in cloud computing
An evaluation of the use of in-memory databases for real-time data processing in patient monitoring
Comparing the effects of database tuning and optimization approaches in improving database performance and efficiency in omnichannel retailing

Topics & Ideas: Human-Computer Interaction

An analysis of the impact of mobile technology on human-computer interaction prevalence in adolescent men
An exploration of how artificial intelligence is changing human-computer interaction patterns in children
An evaluation of the usability and accessibility of web-based systems for CRM in the fast fashion retail sector
Assessing the influence of virtual and augmented reality on consumer purchasing patterns
An examination of the use of gesture-based interfaces in architecture
Exploring the impact of ease of use in wearable technology on geriatric user
Evaluating the ramifications of gamification in the Metaverse
A systematic review of user experience (UX) design advances associated with Augmented Reality
A comparison of natural language processing algorithms automation of customer response Comparing end-user perceptions of natural language processing algorithms for automated customer response
Analysing the impact of voice-based interfaces on purchase practices in the fast food industry

Research Topic Kickstarter - Need Help Finding A Research Topic?

Topics & Ideas: Information Security

A bibliometric review of current trends in cryptography for secure communication
An analysis of secure multi-party computation protocols and their applications in cloud-based computing
An investigation of the security of blockchain technology in patient health record tracking
A comparative study of symmetric and asymmetric encryption algorithms for instant text messaging
A systematic review of secure data storage solutions used for cloud computing in the fintech industry
An analysis of intrusion detection and prevention systems used in the healthcare sector
Assessing security best practices for IoT devices in political offices
An investigation into the role social media played in shifting regulations related to privacy and the protection of personal data
A comparative study of digital signature schemes adoption in property transfers
An assessment of the security of secure wireless communication systems used in tertiary institutions

Topics & Ideas: Software Engineering

A study of agile software development methodologies and their impact on project success in pharmacology
Investigating the impacts of software refactoring techniques and tools in blockchain-based developments
A study of the impact of DevOps practices on software development and delivery in the healthcare sector
An analysis of software architecture patterns and their impact on the maintainability and scalability of cloud-based offerings
A study of the impact of artificial intelligence and machine learning on software engineering practices in the education sector
An investigation of software testing techniques and methodologies for subscription-based offerings
A review of software security practices and techniques for protecting against phishing attacks from social media
An analysis of the impact of cloud computing on the rate of software development and deployment in the manufacturing sector
Exploring the impact of software development outsourcing on project success in multinational contexts
An investigation into the effect of poor software documentation on app success in the retail sector

CompSci & IT Dissertations/Theses

While the ideas we’ve presented above are a decent starting point for finding a CompSci-related research topic, they are fairly generic and non-specific. So, it helps to look at actual dissertations and theses to see how this all comes together.

Below, we’ve included a selection of research projects from various CompSci-related degree programs to help refine your thinking. These are actual dissertations and theses, written as part of Master’s and PhD-level programs, so they can provide some useful insight as to what a research topic looks like in practice.

An array-based optimization framework for query processing and data analytics (Chen, 2021)
Dynamic Object Partitioning and replication for cooperative cache (Asad, 2021)
Embedding constructural documentation in unit tests (Nassif, 2019)
PLASA | Programming Language for Synchronous Agents (Kilaru, 2019)
Healthcare Data Authentication using Deep Neural Network (Sekar, 2020)
Virtual Reality System for Planetary Surface Visualization and Analysis (Quach, 2019)
Artificial neural networks to predict share prices on the Johannesburg stock exchange (Pyon, 2021)
Predicting household poverty with machine learning methods: the case of Malawi (Chinyama, 2022)
Investigating user experience and bias mitigation of the multi-modal retrieval of historical data (Singh, 2021)
Detection of HTTPS malware traffic without decryption (Nyathi, 2022)
Redefining privacy: case study of smart health applications (Al-Zyoud, 2019)
A state-based approach to context modeling and computing (Yue, 2019)
A Novel Cooperative Intrusion Detection System for Mobile Ad Hoc Networks (Solomon, 2019)
HRSB-Tree for Spatio-Temporal Aggregates over Moving Regions (Paduri, 2019)

Looking at these titles, you can probably pick up that the research topics here are quite specific and narrowly-focused , compared to the generic ones presented earlier. This is an important thing to keep in mind as you develop your own research topic. That is to say, to create a top-notch research topic, you must be precise and target a specific context with specific variables of interest . In other words, you need to identify a clear, well-justified research gap.

Fast-Track Your Research Topic

If you’re still feeling a bit unsure about how to find a research topic for your Computer Science dissertation or research project, check out our Topic Kickstarter service.

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Research topics and ideas about data science and big data analytics

Investigating the impacts of software refactoring techniques and tools in blockchain-based developments.

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Five Hundred Most-Cited Papers in the Computer Sciences: Trends, Relationships and Common Factors

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First Online: 29 March 2021
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Phoey Lee Teh ORCID: orcid.org/0000-0002-7787-1299 19 &
Peter Heard ORCID: orcid.org/0000-0002-5135-7822 20

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1366))

Included in the following conference series:

World Conference on Information Systems and Technologies

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This study reveals common factors among highly cited papers in the computer sciences. The 500 most cited papers in the computer sciences published between January 2013 and December 2017 were downloaded from the Web of Science (WoS). Data on the number of citations, number of authors, article length and subject sub-discipline were extracted and analyzed in order to identify trends, relationships and common features. Correlations between common factors were analyzed. The 500 papers were cited a total of 10,926 times: the average number of citations per paper was 21.82 citations. A correlation was found between author credibility (defined in terms of the QS University Ranking of the first named author’s affiliation) and the number of citations. Authors from universities ranked 350 or higher were more cited than those from lower ranked universities. Relationships were also found between journal ranking and both the number of authors and the article length. Higher ranked journals tend to have a greater number of authors, but were of shorter length. The article length was also found to be correlated with the number of authors and the QS Subject Ranking of the first author’s affiliation. The proportion of articles in higher ranked journals (journal quartile), the length of articles and the number of citations per page were all found to correlate to the sub-discipline area (Information Systems; Software Engineering; Artificial Intelligence; Interdisciplinary Applications; and Theory and Methods).

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Department of Computing and Information Systems, School of Science and Technology, Sunway University, 47500, Sunway City, Malaysia

Phoey Lee Teh

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Peter Heard

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Álvaro Rocha

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Hojjat Adeli

Institute of Data Science and Digital Technologies, Vilnius University, Vilnius, Lithuania

Gintautas Dzemyda

DCT, Universidade Portucalense, Porto, Portugal

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Department of Information Sciences, University of Sheffield, Lisbon, Portugal

Ana Maria Ramalho Correia

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Teh, P.L., Heard, P. (2021). Five Hundred Most-Cited Papers in the Computer Sciences: Trends, Relationships and Common Factors. In: Rocha, Á., Adeli, H., Dzemyda, G., Moreira, F., Ramalho Correia, A.M. (eds) Trends and Applications in Information Systems and Technologies . WorldCIST 2021. Advances in Intelligent Systems and Computing, vol 1366. Springer, Cham. https://doi.org/10.1007/978-3-030-72651-5_2

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12 Most Emerging Research Areas in Computer Science in 2021

By: P. Chaudhary, B. Gupta

Artificial Intelligence and Robotics

Artificial Intelligence and Robotics [1, 2] field aims at developing computational system that are intelligent in decision making, planning, object recognition, and other complex computational tasks that require minimum human intervention. This field emphasizes upon the development of cognitive algorithms for a variety of domains including e-commerce, healthcare, transport, manufacturing, gaming, defense industry, logistics, to name a few. It includes the application of popular emerging technologies such as Deep leaning, machine learning, Natural language processing (NLP), robotics, evolutionary algorithms, statistical inference, probabilistic methods, and computer vision. Some of the eminent research areas includes the following:

Knowledge representation and reasoning
Estimation theory
Mobility mechanisms
Multi-agent negotiation
Intelligent agents
Semantic segmentation
Assistive robotics in medical diagnosis
Robot perception and learning
Motion planning and control
Autonomous vehicles
Personal assistive robots
Search and information retrieval
Speech and language recognition
Fuzzy and neural system
Intelligent embedded system in industries
Object detection and capturing
Intelligent information systems

2. Big Data Analytics

Big data analytics [3, 4] research field involves design and development of techniques/algorithms/frameworks to explore the large amount of data to fulfill organization’s objectives. This area includes mathematical, statistical and graphical approaches to mine useful knowledge patterns from heterogeneous raw data. It is one of the potential and emerging research domains as almost every organization is attempting to utilize available data to enhance their productivity and services to their customers. Some of the distinguished research areas are following:

Predictive analysis
Data capturing and transmission
Parallel Data processing
Uncertainty in data
Data anonymization methods
Data processing in distributed environment
Privacy protecting techniques
Semantic analysis on social media
Intelligent traffic surveillance
Topological data analysis

3. Biometrics and Computational Biology

This field embraces enormous potential for researchers as it amalgamates multiple research areas including big data, image processing, biological science, data mining, and machine learning. This field emphasizes on the designing and development of computational techniques for processing biological data [5, 6]. Some of the potential research areas includes:

Structure and sequence analysis algorithms
Protein structure anticipation
Data modeling of scientific applications
Virtual screening
Brain image analysis using data mining approaches
Design predictive models for severe disease analysis
Molecular structure modeling and analysis
Brain-machine interfaces
Computational neuroscience

4. Data Mining and Databases

This field motivates research on designing vital methods, prototype schemes and applications in data mining and databases. This field ensembles all methods, techniques, and algorithms used for extracting knowledgeable information from the available heterogenous raw data [7, 8]. It enables classification, characterization, searching and clustering different datasets from wide range of domains including e-commerce, social media, healthcare, to name a few. This field demands parallel and distributed processing of data as it operates on massive quantity of data. It integrates various research domains including artificial intelligence, big data analytics, data mining, database management system, and bioinformatics. Some of the eminent research areas comprises as follows:

Distributed data mining
Multimedia storage and retrieval
Data clustering
Pattern matching and analysis
High-dimensional data modeling
Spatial and scientific data mining for sensor data
Query interface for text/image processing
Scalable data analysis and query processing
Metadata management
Graph database management and analysis system for social media
Interactive data exploration and visualization
Secure data processing

5. Internet of Things (IoTs)

Internet of Things has transformed the lives of people through exploring new horizons of networking. It connects physical objects with the internet as per the application to serve the user. This field carries enormous potential in different research areas related to the IoT and its interrelated research domains [9, 10]. These areas include as follows:

IoT network infrastructure design
Security issues in IoT
Architectural issues in Embedded system
Adaptive networks for IoT
Service provisioning and management in IoT
Middleware management in IoT
Handling Device Interoperability in IoT
Scalability issues in IoT
Privacy and trust issues in IoT
Data storage and analysis in IoT networks
Integration of IoT with other emerging technologies such as fog computing, SDN, Blockchain, etc.
Context and location awareness in IoT networks
Modeling and management of IoT applications
Task scheduling in IoT networks
Resource allotment among smart devices in IoT networks.

6. High-Performance Computing

This field encourage the research in designing and development of parallel algorithms/techniques for multiprocessor and distributed systems. These techniques are efficient for data and computationally exhaustive programs like data mining, optimization, super computer application, graph portioning, to name a few [11, 12]. Some of the eminent research challenges includes the following:

Information retrieval methods in cloud storage
Graph mining in social media networks
Distributed and parallel computing methods
Development of architecture aware algorithms
Big data analytics methods on GPU system
Designing of parallel algorithms
Designing of algorithms for Quantum computing

7. Blockchain and Decentralized Systems

This field [13, 14] revolutionize the digital world through processing network information without any central authority. This field is an emerging computing paradigm and motivates the design and development of algorithms that operate in decentralized environment. These techniques provide security, robustness and scalability in the network. Some of the eminent research areas includes the following:

Enhancing IoT security using blockchain
Precision agriculture and blockchain
Social blockchain networks
Blockchain based solutions for intelligent transportation system
Security and privacy issues in blockchain networks
Digital currencies and blockchain
Blockchain and 5G/6G communication networks
Integration of cloud/fog computing with blockchain
Legislation rules and policies for blockchain
Artificial Intelligence for blockchain system

8. Cybersecurity

With the development of new technology such as IoT, attackers have wider attack surface to halt the normal functioning of any network. Attackers may have several intentions to trigger cyber-attacks either against an individual person, organization, and/or a country. Now-a-days, we are living in a digital world where everything is connected is to the internet, so we are prone to some form of security attacks [15, 16]. This field carries massive potential for research on different techniques/methods to defend against these attacks. Some of the emerging research areas comprise the following:

Intrusion detection system
Applied cryptography
Privacy issues in RFID system
Security challenges in IoT system
Malware detection in cloud computing
Security and privacy issues in social media
Wireless sensor network security
Mobile device security
Lawa and ethics in cybersecurity
Cyber physical system security
Software defined network security
Security implications of the quantum computing
Blockchain and its security
AI and IoT security
Privacy issues in big data analytics
Phishing detection in finance sector

9. AI and Cyber Physical System

Specifically, Cyber physical system integrates computation and physical methods whose functionalities is determined by both physical and cyber component of the system. Research in this area motivates the development of tools, techniques, algorithms and theories for the CPS and other interrelated research domains [17, 18]. Research topics includes the following:

Human computer interaction
Digital design of CPS interfaces
Embedded system and its security
Industrial Interne to things
Automation in manufacturing industries
Robotics in healthcare sector
Medical informatics
AI, robotics and cyber physical system
Robot networks
Cognitive computing and CPS

10. Networking and Embedded Systems

This field [19, 20] encourages research on the designing of contemporary theories and approaches, effective and scalable methods and protocols, and innovative network design structure and services. These mechanisms improve the reliability, availability, security, privacy, manageability of current and future network and embedded systems. Research in this domain comprises of following topics:

Cyber physical system
Design of novel network protocols
Cognitive radio networks
Network security for lightweight and enterprise networks
Resource allocation schemes in resource-constrained networks
Network coding
Energy efficient protocols for wireless sensor networks
AI and embedded system
Embedded system for precision agriculture

11. Computer Vision and Augmented Reality

Computer vision [21, 22] is a multidisciplinary field that make computer system to understand and extract useful information from digital images and videos. This field motivates the research in designing the tools and techniques for understanding, processing, extracting, and storing, analyzing the digital images and videos. It embraces multiple domains such as image processing, artificial intelligence, pattern recognition, virtual reality, augmented reality, semantic structuring, statistics, and probability. Some of the eminent research topics includes the following:

Computer vision for autonomous robots
Object detection in autonomous vehicles
Object detection and delineation in UAVs network.
Biomedical image analysis
Augmented reality in gaming
Shape analysis in digital images
Computer vision for forensics
Robotics navigation
Deep learning techniques for computer vision
Automation in manufacturing sector
3D object recognition and tracking

12. Wireless Networks and Distributed Systems

The research in this field emphasizes on the developments of techniques that facilitate communication and maintain coordination among distributed nodes in a network [23, 24]. It is a broad area that embraces numerous domains including cloud computing, wireless networks, mobile computing, big data, and edge computing. Some of the eminent research topics includes the following:

Message passing models in distributed system
Parallel distributed computing
Fault tolerance and load balancing
Dynamic resource allocation in distributed system
Resource discovery and naming
Low-latency consistency protocols
Designing of consensus protocols
Efficient communication protocols in distributed system
Security issues in distributed networks
Privacy and trust models
Optimization of distributed storage
Distributed and federated machine learning

[1] Wisskirchen, G., Biacabe, B. T., Bormann, U., Muntz, A., Niehaus, G., Soler, G. J., & von Brauchitsch, B. (2017). Artificial intelligence and robotics and their impact on the workplace . IBA Global Employment Institute, 11(5), 49-67. [2] Kortenkamp, D., Bonasso, R. P., & Murphy, R. (Eds.). (1998). Artificial intelligence and mobile robots: case studies of successful robot systems. MIT Press. [3] Dai, H. N., Wang, H., Xu, G., Wan, J., & Imran, M. (2020). Big data analytics for manufacturing internet of things: opportunities, challenges and enabling technologies . Enterprise Information Systems, 14(9-10), 1279-1303. [4] Müller, O., Junglas, I., Vom Brocke, J., & Debortoli, S. (2016). Utilizing big data analytics for information systems research: challenges, promises and guidelines . European Journal of Information Systems, 25(4), 289-302. [5] Waterman, M. S. (2018). Introduction to computational biology: maps, sequences and genomes. Chapman and Hall/CRC. [6] Imaoka, H., Hashimoto, H., Takahashi, K., Ebihara, A. F., Liu, J., Hayasaka, A., … & Sakurai, K. (2021). The future of biometrics technology: from face recognition to related applications. APSIPA Transactions on Signal and Information Processing, 10. [7] Zhu, X., & Davidson, I. (Eds.). (2007). Knowledge Discovery and Data Mining: Challenges and Realities: Challenges and Realities . Igi Global. [8] Tseng, L., Yao, X., Otoum, S., Aloqaily, M., & Jararweh, Y. (2020). Blockchain-based database in an IoT environment: challenges, opportunities, and analysis. Cluster Computing, 23(3), 2151-2165. [9] Stoyanova, M., Nikoloudakis, Y., Panagiotakis, S., Pallis, E., & Markakis, E. K. (2020). A survey on the internet of things (IoT) forensics: challenges, approaches, and open issues. IEEE Communications Surveys & Tutorials, 22(2), 1191-1221. [10] Nižetić, S., Šolić, P., González-de, D. L. D. I., & Patrono, L. (2020). Internet of Things (IoT): Opportunities, issues and challenges towards a smart and sustainable future. Journal of Cleaner Production, 274, 122877. [11] Hager, G., & Wellein, G. (2010). Introduction to high performance computing for scientists and engineers. CRC Press. [12] Wang, G. G., Cai, X., Cui, Z., Min, G., & Chen, J. (2017). High performance computing for cyber physical social systems by using evolutionary multi-objective optimization algorithm . IEEE Transactions on Emerging Topics in Computing, 8(1), 20-30. [13] Zheng, Z., Xie, S., Dai, H. N., Chen, X., & Wang, H. (2018). Blockchain challenges and opportunities: A survey. International Journal of Web and Grid Services, 14(4), 352-375. [14] Nguyen, D. C., Ding, M., Pham, Q. V., Pathirana, P. N., Le, L. B., Seneviratne, A., … & Poor, H. V. (2021). Federated learning meets blockchain in edge computing: Opportunities and challenges . IEEE Internet of Things Journal. [15] Tawalbeh, L. A., Muheidat, F., Tawalbeh, M., & Quwaider, M. (2020). IoT Privacy and security: Challenges and solutions. Applied Sciences, 10(12), 4102. [16] Boubiche, D. E., Athmani, S., Boubiche, S., & Toral-Cruz, H. (2021). Cybersecurity Issues in Wireless Sensor Networks: Current Challenges and Solutions. Wireless Personal Communications, 117(1). [17] Gupta, R., Tanwar, S., Al-Turjman, F., Italiya, P., Nauman, A., & Kim, S. W. (2020). Smart contract privacy protection using ai in cyber-physical systems: Tools, techniques and challenges. IEEE Access, 8, 24746-24772. [18] Kravets, A. G., Bolshakov, A. A., & Shcherbakov, M. V. (2020). Cyber-physical Systems: Industry 4.0 Challenges . Springer. [19] Duan, Q., Wang, S., & Ansari, N. (2020). Convergence of networking and cloud/edge computing: Status, challenges, and opportunities. IEEE Network, 34(6), 148-155. [20] Wang, C. X., Di Renzo, M., Stanczak, S., Wang, S., & Larsson, E. G. (2020). Artificial intelligence enabled wireless networking for 5G and beyond: Recent advances and future challenges. IEEE Wireless Communications, 27(1), 16-23. [21] Chen, C. H. (Ed.). (2015). Handbook of pattern recognition and computer vision . World Scientific. [22] Esteva, A., Chou, K., Yeung, S., Naik, N., Madani, A., Mottaghi, A., … & Socher, R. (2021). Deep learning-enabled medical computer vision. NPJ digital medicine, 4(1), 1-9. [23] Farahani, B., Firouzi, F., & Luecking, M. (2021). The convergence of IoT and distributed ledger technologies (DLT): Opportunities, challenges, and solutions. Journal of Network and Computer Applications, 177, 102936. [24] Alfandi, O., Otoum, S., & Jararweh, Y. (2020, April). Blockchain solution for iot-based critical infrastructures: Byzantine fault tolerance. In NOMS 2020-2020 IEEE/IFIP Network Operations and Management Symposium (pp. 1-4). IEEE.

Cite this article:

P. Chaudhary, B. Gupta (2021) 12 Most Emerging Research Areas in Computer Science in 2021 , Insights2Techinfo, pp. 1

FAQ on this topic

Artificial Intelligence and Robotics, Big Data Analytics, Biometrics and Computational Biology, Data Mining and Databases, Internet of Things (IoTs), High-Performance Computing, Blockchain and Decentralized Systems,Cybersecurity

Big data research field involves design and development of techniques/algorithms/frameworks to explore the large amount of data to fulfill organization’s objectives. Some of the distinguished research areas are following: Data capturing and transmission, Parallel Data processing,Data anonymization methods,Data processing in distributed environment

Artificial Intelligence field aims at developing computational systems that are intelligent in decision making, planning, object recognition, and other complex computational tasks that require minimum human intervention. Some of the eminent research areas includes the following: Knowledge representation and reasoning Autonomous vehicles, Fuzzy and neural system, Intelligent information systems

Some of the eminent research areas comprises as follows:Distributed data mining, Multimedia storage and retrieval, Data clustering, Pattern matching and analysis, High-dimensional data modeling, Spatial and scientific data mining for sensor data.

The research areas in IoT include as follows: IoT network infrastructure design, Security issues in IoT,Architectural issues in Embedded system, Service provisioning and management in IoT, Middleware management in IoT

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Computerworld

25 of today’s coolest network and computing research projects

Latest concoctions from university labs include language learning website, a newfangled internet for mobile devices and even ip over xylophones.

University labs, fueled with millions of dollars in funding and some of the biggest brains around, are bursting with new research into computer and networking technologies.

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networks, computer and a general focus on shrinking things and making them faster are among the hottest areas, with some advances already making their way into the market. Here’s a roundup of 25 such projects that caught our eyes:

This free website, Duolingo, from a pair of Carnegie Mellon University computer scientists serves double duty: It helps people learn new languages while also translating the text on Web pages into different languages.

CMU’s Luis von Ahn and Severin Hacker have attracted more than 100,000 people in a beta test of the system, which initially offered free language lessons in English, Spanish, French and German, with the computer offering advice and guidance on unknown words. Using the system could go a long way toward translating the Web, many of whose pages are unreadable by those whose language skills are narrow.

Von Ahn is a veteran of such crowdsourcing technologies, having created online reCAPTCHA puzzles to cut down on spam while simultaneously digitizing old books and periodicals. Von Ahn’s spinoff company, reCAPTCHA, was acquired by Google in 2009. Duolingo, spun off in November to offer commercial and free translation services, received $3.3 million in funding from Union Square Ventures, actor Ashton Kutcher and others.

Princeton University Computer Science researchers envision an Internet that is more flexible for operators and more useful to mobile users. Princeton’s Serval system is what Assistant Professor of Computer Science Michael Freedman calls a Service Access Layer that sits between the IP Network Layer (Layer 3) and Transport Layer (Layer 4), where it can work with unmodified network devices. Serval’s purpose is to make Web services such as Gmail and Facebook more easily accessible, regardless of where an end user is, via a services naming scheme that augments what the researchers call an IP address set-up “designed for communication between fixed hosts with topology-dependent addresses.” Data center operators could benefit by running Web servers in virtual machines across the cloud and rely less on traditional load balancers.

Serval, which Freedman describes as a “replacement” technology, will likely have its first production in service-provider networks. “Its largest benefits come from more dynamic settings, so its features most clearly benefit the cloud and mobile spaces,” he says.

If any of this sounds similar to software-defined networking (SDN), there are in fact connections. Freedman worked on an SDN/OpenFlow project at Stanford University called Ethane that was spun out into a startup called Nicira for which VMware recently plunked down $1.26 billion.

WiFi routers to the rescue

Researchers at Germany’sTechnical University in Darmstadt have described a way for home Wi-Fi routers to form a backup mesh network to be used by the police, firefighters and other emergency personnel in the case of a disaster or other incident that wipes out standard cell and phone systems.

The proliferation of Wi-Fi routers makes the researchers confident that a dense enough ad hoc network could be created, but they noted that a lack of unsecured routers would require municipalities to work with citizens to allow for the devices to be easily switched into emergency mode. The big question is whether enough citizens would really allow such access, even if security was assured.

Hyperspeed signaling

University of Tulsa engineers want to slow everything down, for just a few milliseconds, to help network administrations avoid cyberattacks.

By slowing traffic, the researchers figure more malware can be detected and then headed off via an algorithm that signals at hyperspeed to set up defenses. Though researcher Sujeet Shenoi told the publication New Scientist that it might not be cheap to set up such a defense system, between the caching system and reserved data pipes needed to support the signals.

Control-Alt-Hack

University of Washington researchers have created a card game called Control-Alt-Hack that’s designed to introduce computer science students to security topics.

The game, funded in part by Intel Labs and the National Science Foundation, made its debut at the Black Hat security conference in Las Vegas over the summer. The tabletop game involves three to six players working for an outfit dubbed Hackers, Inc., that conducts security audits and consulting, and players are issued challenges, such as hacking a hotel mini bar payment system or wireless medical implant, or converting a robotic vacuum cleaner into a toy. The game features cards (including descriptions of well-rounded hackers who rock climb, ride motorcycles and do more than sit at their computers), dice, mission cards, “hacker cred tokens” and other pieces, and is designed for players ages 14 and up. It takes about an hour to play a game. No computer security degree needed.

“We went out of our way to incorporate humor,” said co-creator Tamara Denning, a UW doctoral student in computer science and engineering, referring to the hacker descriptions and challenges on the cards. “We wanted it to be based in reality, but more importantly we want it to be fun for the players.”

Ghost-USB-Honeypot project

This effort, focused on nixing malware like Flame that spreads from computer to computer via USB storage drives, got its start based on research from Sebastian Poeplau at Bonn University’s Institute of Computer Science. Now it’s being overseen by the broader Honeynet Project.

The breakthrough by Poeplau and colleagues was to create a virtual drive that runs inside a USB drive to snag malware . According to the project website: “Basically, the honeypot emulates a USB storage device. If your machine is infected by malware that uses such devices for propagation, the honeypot will trick it into infecting the emulated device.”

One catch: the security technology only works on XP 32 bit, for starters.

IP over Xylophone Players (IPoXP)

Practical applications for running IP over xylophones might be a stretch, but doing so can teach you a few things about the truly ubiquitous protocol.

A University of California Berkeley researcher named R. Stuart Geiger led this project, which he discussed earlier this year at the Association for Computing Machinery’s Conference on Human Factors in Computing Systems . Geiger’s Internet Protocol over Xylophone Players (IPoXP) provides a fully compliant IP connection between two computers. His setup uses a pair of Arduino microcontrollers, some sensors, a pair of xylophones and two people to play the xylophones.

The exercise provided some insights into the field of Human-Computer Interaction (HCI). It emulates a technique HCI specialists use to design interfaces called umwelt, which is a practice of imagining what the world must look like to the potential users of the interface. This experiment allowed participants to get the feel for what it would be like to be a circuit.

“I don’t think I realized how robust and modular the OSI model is,” Geiger said. “The Internet was designed for much more primitive technologies, but we haven’t been able to improve on it, because it is such a brilliant model.”

Making software projects work

San Francisco State University and other researchers are puzzling over why so many software projects wind up getting ditched, fail or get completed, but late and over budget. The key, they’ve discovered, is rethinking how software engineers are trained and managed to ensure they can work as teams.

The researchers, also from Florida Atlantic University and Fulda University in Germany, are conducting a National Science Foundation-funded study with their students that they hope will result in a software model that can predict whether a team is likely to fail. Their study will entail collecting information on how often software engineering students – teamed with students at the same university and at others — meet, email each other, etc.

“We want to give advice to teachers and industry leaders on how to manage their teams,” says Dragutin Petkovic, professor and chair of SF State’s Computer Science Department. “Research overwhelmingly shows that it is ‘soft skills,’ how people work together, that are the most critical to success.”

Ultra low-power wireless

Forget about 3G, 4G and the rest: University of Arkansas engineering researchers are focused on developing very low-power wireless systems that can grab data from remote sensors regardless of distortion along the network path.

These distortion-tolerant systems would enable sensors, powered by batteries or energy-harvesting, to remain in the field for long periods of time and withstand rough conditions to monitor diverse things such as tunnel stability and animal health. By tolerating distortion, the devices would expend less energy on trying to clean up communications channels.

“If we accept the fact that distortion is inevitable in practical communication systems, why not directly design a system that is naturally tolerant to distortion?” says Jingxian Wu, assistant professor of electrical engineering.

The National Science Foundation is backing this research with $280,000 in funding.

2-way wireless

University of Waterloo engineering researchers have developed a way for wireless voice and data signals to be sent and received simultaneously on a single radio channel frequency, a breakthrough they say could make for better performing, more easily connected and more secure networks.

“This means wireless companies can increase the bandwidth of voice and data services by at least a factor of two by sending and receiving at the same time, and potentially by a much higher factor through better adaptive transmission and user management in existing networks,” said Amir Khandani, a Waterloo electrical and computer engineering professor, in a statement. He says the cost for hardware and antennas to support such a system wouldn’t cost any more than for current one-way systems.

Next up is getting industry involved in bringing such technology into the standards process.

Next steps require industry involvement by including two-way in forthcoming standards to enable wide spread implementation.

The Waterloo research was funded in part by the Canada Foundation for Innovation and the Ontario Ministry of Research and Innovation.

Spray-on batteries

Researchers at Rice University in Houston have developed a prototype spray-on battery that could allow engineers to rethink the way portable electronics are designed.

The rechargeable battery boasts similar electrical characteristics to the lithium ion batteries that power almost every mobile gadget, but it can be applied in layers to almost any surface with a conventional airbrush, said Neelam Singh, a Rice University graduate student who led a team working on the technology for more than a year.

Current lithium ion batteries are almost all variations on the same basic form: an inflexible block with electrodes at one end. Because they cannot easily be shaped, they sometimes restrict designers, particularly when it comes to small gadgets with curved surfaces, but the Rice prototypes could change that. “Today, we only have a few form factors of batteries, but this battery can be fabricated to fill the space available,” said Singh.

The battery is sprayed on in five layers: two current collectors sandwich a cathode, a polymer separator and an anode. The result is a battery that can be sprayed on to plastics, metal and ceramics.

The researchers are hoping to attract interest from electronics companies, which Singh estimates could put it into production relatively easily. “Airburshing technology is well-established. At an industrial level it could be done very fast,” she said.

Mobile Mosh pit

Two MIT researchers formally unveiled over the summer a protocol called State Synchronization Protocol (SSP) and a remote log-in program using it dubbed Mosh (for mobile shell) that’s intended as an alternative to Secure Shell (SSH) for ensuring good connectivity for mobile clients even when dealing with low bandwidth connections. SSP and Mosh have been made available for free, on GNU/, FreeBSD and OS X, via an MIT website.

SSH, often used by network and system admins for remotely logging into servers, traditionally connects computers via TCP, but it’s that use of TCP that creates headaches for mobile users, since TCP assumes that the two endpoints are fixed, says Keith Winstein, a graduate student with MIT’s Computer Science and Artificial Intelligence Lab (CSAIL), and Mosh’s lead developer. “This is not a great way to do real-time communications,” Winstein says. SSP uses UDP, a connectionless, stateless transport mechanism that could be useful for stabilizing mobile usage of apps from Gmail to Skype.

Network Coding

Researchers from MIT, California Institute of Technology and University of Technology in Munich are putting network coding and error-correction coding to use in an effort to measure capacity of wired, and more challengingly, even small wireless networks (read their paper here for the gory details).

The researchers have figured out a way to gauge the upper and lower bounds of capacity in a wireless network. Such understanding could enable enterprises and service providers to design more efficient networks regardless of how much noise is on them (and wireless networks can get pretty darn noisy).

More details from MIT press office.

100 terahertz level

A University of Pittsburgh research team is claiming a communications breakthrough that they say could be used to speed up electronic devices such as and laptops in a big way. Their advance is a demonstrated access to more than 100 terahertz of bandwidth (electromagnetic spectrum between infrared and microwave light), whereas electronic devices traditionally have been limited to bandwidth in the gigahertz realm.

Researchers Hrvoje Petek of the University of Pittsburgh and visiting professor Muneaki Hase of the University of Tsukuba in Japan, have published their NSF-funded research findings in a paper in Nature Photonics. The researchers “detail their success in generating a frequency comb-dividing a single color of light into a series of evenly spaced spectral lines for a variety of uses-that spans a more than 100 terahertz bandwidth by exciting a coherent collective of atomic motions in a semiconductor silicon crystal.”

Petek says the advance could result in devices that carry a thousand-fold more information.

Separately, IBM researchers have developed a prototype optical chip that can transfer data at 1Tbps, the equivalent of downloading 500 high-definition movies, using light pulses rather than by sending electrons over wires.

The Holey Optochip is described as a parallel optical transceiver consisting of a transmitter and a receiver, and designed to handle gobs of data on corporate and consumer networks.

Cooling off with graphene

Graphene is starting to sound like a potential wonder material for the electronics business. Researchers from the University of California at Riverside, the University of Texas at Dallas and Austin, and Xiamen University in China have come up with a way to engineer graphene so that it has much better thermal properties. Such an isotopically-engineered version of graphene could be used to build cooler-running laptops, wireless gear and other equipment. The need for such a material has grown as electronic devices have gotten more powerful but shrunk in size.

“The important finding is the possibility of a strong enhancement of thermal conduction properties of isotopically pure graphene without substantial alteration of electrical, optical and other physical properties,” says UC Riverside Professor of Electrical Engineering Alexander Balandin, in a statement. “Isotopically pure graphene can become an excellent choice for many practical applications provided that the cost of the material is kept under control.”

Such a specially engineered type of graphene would likely first find its way into some chip packaging materials as well into photovoltaic solar cells and flexible displays, according to UC Riverside. Beyond that, it could be used with silicon in computer chips, for interconnect wiring to to spread heat.

Industry researchers have been making great strides on the graphene front in recent years. IBM, for example, last year said it had created the first graphene-based integrated circuit. Separately, two Nobel Prize winning scientists out of the U.K. have come up with a new way to use graphene – the thinnest material in the world – that could make Internet pipes feel a lot fatter.

Keeping GPS honest

Cornell University researchers are going on the offense against those who would try to hack GPS systems like those used in everything from cars to military drones to cellphone systems and power grids. Over the summer, Cornell researchers tested their system for outsmarting GPS spoofers during a Department of Homeland Security-sponsored demo involving a mini helicopter in the New Mexico desert at the White Sands Missile Range.

Cornell researchers have come up with GPS receiver modifications that allow the systems to distinguish between real and bogus signals that spoofers would use to trick cars, airplanes and other devices into handing over control. They emphasized that the threat of GPS spoofing is very real, with Iran last year claiming to have downed a GPS-guided American drone using such techniques.

Getting smartphones their ZZZZs

Purdue University researchers have come up with a way to detect smartphone bugs that can drain batteries while they’re not in use.

“These energy bugs are a silent battery killer,” says Y. Charlie Hu, a Purdue University professor of electrical and computer engineering. “A fully charged phone battery can be drained in as little as five hours.”

The problem is that app developers aren’t perfect when it comes to building programs that need to perform functions when phones are asleep and that use APIs provided by smartphone makers. The researchers, whose work is funded in part by the National Science Foundation, investigated the problem on Android phones, and found that about a quarter of some 187 apps contained errors that could drain batteries. The tools they’re developing to detect such bugs could be made available to developers to help them cut down on battery-draining mistakes.

Quantum leap in search

University of Southern California and University of Waterloo researchers are exploring how quantum computing technology can be used to speed up the math calculations needed to make Internet search speedy even as the gobs of data on the Web expands.

The challenge is that Google’s page ranking algorithm is considered by some to be the largest numerical calculation carried out worldwide, and no quantum computer exists to handle that. However, the researchers have created models of the web to simulate how quantum computing could be used to slice and dice the Web’s huge collection of data. Early findings have been encouraging, with quantum computers shown through the models to be faster at ranking the most important pages and improving as more pages needed to be ranked.

The research was funded by the NSF, NASA Ames Research Center, Lockheed Martin’s University Research Initiative and a Google faculty research award.

Sharing malware in a good way

Georgia Tech Research Institute security specialists have built a system called Titan designed to help corporate and government officials anonymously share information on malware attacks they are fighting, in hopes of fighting back against industrial espionage.

The threat analysis system plows through a repository of some 100,000 pieces of malicious code per day, and will give contributors quick feedback on malware samples that can be reverse-engineered by the Titan crew. Titan will also alert members of new threats, such as targeted spear-phishing attacks, and will keep tabs on not just Windows threats, but also those to MacIntosh and iOS, and Google Android systems.

“As a university, Georgia Tech is uniquely positioned to take this white hat role in between industry and government,” said Andrew Howard, a GTRI research scientist who is part of the Titan project . “We want to bring communities together to break down the walls between industry and government to provide a trusted, sharing platform.”

Touch-feely computing

Researchers from the University of Notre Dame, MIT and the University of Memphis are working on educational software that can respond to students’ cognitive and emotional states, and deliver the appropriate content based on how knowledgeable a student is about a subject, or even how bored he or she is with it.

AutoTutor and Affective AutoTutor get a feel for students’ mood and capabilities based on their responses to questions, including their facial expressions, speech patterns and hand movements.

“Most of the 20th-century systems required humans to communicate with computers through windows, icons, menus and pointing devices,” says Notre Dame Assistant Professor of Psychology Sidney D’Mello, an expert in human-computer interaction and AI in education . “But humans have always communicated with each other through speech and a host of nonverbal cues such as facial expressions, eye contact, posture and gesture. In addition to enhancing the content of the message, the new technology provides information regarding the cognitive states, motivation levels and social dynamics of the students.”

Mobile nets on the move

For emergency responders and others who need to take their mobile networks with them, even in fast-moving vehicles, data transmission quality can be problematic. North Carolina State University researchers say they’ve come up with a way to improve the quality of these Mobile ad hoc networks (MANET).

“Our goal was to get the highest data rate possible, without compromising the fidelity of the signal,” says Alexandra Duel-Hallen, a professor of electrical and computer engineering at NC State whose work is outlined in the paper “ Enabling Adaptive Rate and Relay Selection for 802.11 Mobile Ad Hoc Networks .”

The challenge is that fast moving wireless nodes make it difficult for relay paths to be identified by the network, as channel power tends to fluctuate much more in fast-moving vehicles. The researchers have come up with an algorithm for nodes to choose the best data relay and transmission paths, based on their experience with recent transmissions.

Tweet the Street

Researchers from the University of California, Riverside and Yahoo Research Barcelona have devised a model that uses data about volumes to predict how financial markets will behave. Their model bested other baseline strategies by 1.4% to 11% and outperformed the Dow Jones Industrial Average during a four-month simulation.

“These findings have the potential to have a big impact on market investors,” said Vagelis Hristidis, an associate professor at the Bourns College of Engineering. “With so much data available from social media, many investors are looking to sort it out and profit from it.”

The research, focused on what Twitter volumes, retweets and who is doing the tweeting might say about individual stocks, differs from that of earlier work focused on making sense of the broader market based on positive and negative sentiments in tweets.

As with so many stock-picking techniques, the researchers here tossed out plenty of caveats about their system, which they said might work quite differently, for example, during a period of overall market growth rather than the down market that their research focused on.

Franken-software

University of Texas, Dallas scientists have developed software dubbed Frankenstein that’s designed to be even more monstrous than the worst malware in the wild so that such threats can be understood better and defended against. Frankenstein can disguise itself as it swipes and messes with data, and could be used as a cover for a virus or other malware by stitching together pieces of such data to avoid antivirus detection methods.

“[Mary] Shelley’s story [about Dr. Frankenstein and his monster] is an example of a horror that can result from science, and similarly, we intend our creation as a warning that we need better detections for these types of intrusions,” said Kevin Hamlen, associate professor of computer science at UT Dallas who created the software, along with doctoral student Vishwath Mohan. “Criminals may already know how to create this kind of software, so we examined the science behind the danger this represents, in hopes of creating countermeasures.”

Such countermeasures might include infiltrating terrorist computer networks, the researchers say. To date, they’ve used the NSF and Air Force Office of Scientific Research-funded technology on benign algorithms, not any production systems.

Safer e-wallets

While e-wallets haven’t quite taken off yet, University of Pittsburgh researchers are doing their part to make potential e-wallet users more comfortable with the near-field communications (NRC) and/or RFID-powered technology.

Security has been a chief concern among potential users, who are afraid thieves could snatch their credit card numbers through the air. But these researchers have come up with a way for e-wallet credit cards to turn on and off, rather than being always on whenever in an electromagnetic field.

“Our new design integrates an antenna and other electrical circuitry that can be interrupted by a simple switch, like turning off the lights in the home or office,” says Marlin Mickle, the Nickolas A. DeCecco Professor of Engineering and executive director of the RFID Center for Excellence in the Swanson School. “The RFID or NFC credit card is disabled if left in a pocket or lying on a surface and unreadable by thieves using portable scanners.”

Mickle claims the advance is both simple and inexpensive, and once the researchers have received what they hope will be patent approval, they expect the technology to be adopted commercially.

Digging into Big Data

The University of California, Berkeley has been handed $10 million by the National Science Foundation as part of a broader $200 million federal government effort to encourage the exploration and better exploitation of massive amounts of information dubbed Big Data collected by far-flung wireless sensors, social media systems and more.

UC Berkeley has five years to use its funds for a project called the Algorithms, Machines and People (AMP) Expedition, which will focus on developing tools to extract important information from Big Data, such as trends that could predict everything from earthquakes to cyberattacks to epidemics.

“Buried within this flood of information are the keys to solving huge societal problems and answering the big questions of science,” said Michael Franklin, director of the AMP Expedition team and a UC Berkeley professor of electrical engineering and computer sciences, in a statement . “Our goal is to develop a new generation of data analysis tools that provide a quantum leap in our ability to make sense of the world around us.”

AMP Expedition researchers are building an open-source software stack called the Berkeley Data Analysis System (BDAS) that boasts large-scale machine-learning and data analysis methods, infrastructure that lets programmers take advantage of cloud and cluster computing, and crowdsourcing (in other words, human intelligence). It builds on the AMPLab formed early last year, with backing from Google, SAP and others.

Bob Brown tracks network research in his and Facebook page, as well on Twitter and Google + .

IDG News Service and other IDG publications contributed to this report

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Interdisciplinary Centers & Initiatives

Computer Science has also grown beyond its own bounds to become a multi-disciplinary field that touches many other sciences as well as arts and humanities: physics, economics, law, management, psychology, biology, medicine, music, philosophy, and linguistics. They have also led to interdisciplinary research centers.

Institute for the Foundations of Data Science

Schools/Departments: CS, S&DS, EE, Econ, Social Science, Political Science, and SOM

Wu-Tsai Institute for Interdisciplinary Neurocognition Research

Schools/Departments: CS, Psych, S&DS, SEAS, and Medicine

Yale Institute for Network Science

Schools/Departments: CS, Social Science, S&DS, and EE

Yale Quantum Institute

Schools/Departments: CS, Applied Physics, Physics, and EE

Computation and Society Initiative

Schools/Departments: CS, S&DS, Social Science

Research Areas

Algorithms and complexity theory .

Yale’s Theory group advances our understanding of the fundamental power and limits of computation and creates innovative algorithms to empower society.

Artificial Intelligence and Machine Learning

We study how to build systems that can learn to solve complex tasks in ways that would traditionally need human intelligence. Our research covers both the foundation and applications of AI: Robotics, Machine Learning Theory, Natural Language Processing, Computer Vision, Human-Computer Interactions, AI for Medicine, and AI for Social Impact.

Computer Architecture

We design the interface of software and hardware of computer systems at all scale – ranging from large-scale AI and cloud services to safety-critical embedded systems to Internet-Of-Things devices. We deliver the next-generation processors to meet performance, power, energy, temperature, reliability, and accuracy goals, by composing principled and well-abstracted hardware.

Computer Graphics

Research in computer graphics at Yale includes sketching, alternative design techniques, texture models, the role of models of human perception in computer graphics, recovering shape and reflectance from images, computer animation, simulation, and geometry processing.

Computer Music

Computer music research at Yale encompasses a range of technical and artistic endeavors.

Computer Networks

Computer networks allow computers to communicate with one another, and provide the fundamental infrastructures supporting our modern society. Research on computer networks at Yale improves on essential network system properties such as efficiency, robustness, and programmability.

Database Systems

Database systems provide an environment for storage and retrieval of both structured and semi-structured data.

Distributed Computing

Distributed computing is the field in computer science that studies the design and behavior of systems that involve many loosely-coupled components. Distributed systems research at Yale includes work in the theory of distributed computing, its programming language support, and its uses to support parallel programming.

Natural Language Processing

Yale scientists conduct cutting-edge research in NLP, including computational liguistics, semantic parsing, multilingual information retrieval, language database interfaces and dialogue systems. We also investigate how to use NLP to create transformative solutions to health care.

Operating Systems

Yale is developing new operating system architectures, application environments, and security frameworks to meet today’s challenges across the computing spectrum, including IoT devices, cyber-physical systems (such as self-driving cars and quadcopters), cloud computers, and blockchain ecosystems.

Programming Languages and Compilers

We approach Programming Languages research from several directions including language design, formal methods, compiler implementation, programming environments, and run-time systems. A major focus of the research at Yale is to build secure, error-free programs, as well as develop frameworks that help others achieve that same goal.

Quantum Computing

Yale has been at the forefront of innovation and discoveries in Quantum Science. Through interdisciplinary research and pioneering innovations, our Yale CS faculty advances the state-of-the-art in quantum computing and quantum information science, building upon insights and lessons from classical computer science.

Robotics research at Yale’s Computer Science department is currently focused on advancing Human-Robot Interaction. Applications include education, manufacturing, entertainment, and service domains. Robots are also used to advance our understanding of human behavior.

Scientific Computing and Applied Math

Scientific computing research at Yale emphasizes algorithm development, theoretical analysis, systems and computer architecture modeling, and programming considerations.

Security and Cryptography

Adequately addressing security and privacy concerns requires a combination of technical, social, and legal approaches. Topics currently under active investigation in the department include mathematical modeling of security properties, implementation and application of cryptographic protocols, secure and privacy-preserving distributed algorithms, trust management, verification of security properties, and proof-carrying code.

Societal and Humanistic Aspects of Computation

Today’s society comprises humans living in a complex and interconnected world that is intertwined with a variety of computing, sensing, and communicating devices. Yale researchers create innovative solutions to mitigate explicit and implicit biases, control polarization, improve diversity, and ensure privacy.

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Research Research Areas

Research areas represent the major research activities in the Department of Computer Science. Faculty and students have developed new ideas to achieve results in all aspects of the nine areas of research.

Choose a research area below to learn more:

Artificial Intelligence and Machine Learning
Human-Computer Interaction and Information Visualization
Computer Engineering (in collaboration with the Electrical and Computer Engineering Department)

Contact Info

Samir Khuller Chair and Professor Phone: 847-491-2748 Email Samir

Computing Research News

This article is published in the October 2022 issue.

On Undergraduate Research in Computer Science: Tips for shaping successful undergraduate research projects

Note: Khuller was the recipient of the 2020 CRA-E Undergraduate Research Faculty Mentoring Award , which recognizes individual faculty members who have provided exceptional mentorship, undergraduate research experiences and, in parallel, guidance on admission and matriculation of these students to research-focused graduate programs in computing. CRA-E is currently accepting nominations for the 2023 award program .

One of the goals I hope to accomplish with this article is to open the eyes of faculty to the ways in which bright and motivated undergraduates can contribute meaningfully to their research projects and groups. This piece intends to help educate folks who have limited experience with undergraduate research or are unsure how to come up with research projects. I hope it helps others learn quickly from the knowledge I have gained over the years.

Exposing undergraduates to research may encourage them to pursue PhDs At the CRA Conference at Snowbird this summer, data was presented that showed that the overall number of PhDs granted in Computer Science (CS) in the US has not changed substantially in the last decade even though undergraduate programs have grown significantly. Meanwhile, the percentage of US students getting PhDs in CS showed a pretty substantial decline from 48% to 31%. While there are many factors at play–notably a strong job market for undergraduates– I do know from prior discussions with undergraduate students (UGs), that many CS departments also do not make a substantial effort in exposing UGs to research opportunities. Moreover, when I started as a faculty member I too struggled in defining good research projects for undergraduates (they were either too easy or too similar to PhD research topics, and so were likely not appropriate for undergraduates). I think getting UGs excited about research is perhaps the first step to getting them excited to think about getting a PhD as a career option.

Is research by undergraduate students an oxymoron? I will admit that initially I too was skeptical about the possibility and success of true undergraduate research. My own research experiences as an undergraduate were pathetic. As a student often I would hear people say “I am going to the library to do research”. So I too went to the library to do research. Research to me meant finding something in the library that was not in a textbook, understanding it, and telling people about the work. At that point I thought I had done some research! I never gave much thought to how new material got into journals to begin with.

Talking to a colleague recently – he said “maybe what all UGs do in a chemistry lab is wash test tubes….”. The truth is that I do not really know what UG research in chemistry looks like. But the point I wanted to make with this article is that high level UG research in CS is entirely doable. Indeed, in theoretical computer science (TCS) we have witnessed brilliant papers in top conferences by undergraduate students, and I would argue that UG research can be done quite effectively in other areas of computing research as well.

So what should UG research in CS look like? I have advised over 30 undergraduate researchers and based on my experiences, I have a few observations. Most successful research projects involving undergraduates require a lead time of about 18 months before graduation. It usually takes a few months for the student to read the relevant papers, and for us to identify a topic that aligns with the student’s interests and background. I usually expect that students would have taken both an undergraduate level class in algorithm design as well as discrete mathematics. If they can take a graduate level class, that would also be incredibly valuable.

Tips for shaping successful undergraduate research projects Below is my process for defining a successful UG research project. UGs typically have 12-18 months for a research project, not 3-4 years like most Ph.D. students.

At my first meeting, I ask the students about the different topics they learned about in their Algorithms class and what appealed to them the most.
Using their answer from bullet #1, I usually spend some time thinking about the right topic for them to work on. The key here is that any paper that the student has to read should not have a long chain of preceding papers that will take them months to get to. Luckily many graph problems as well as combinatorial optimization and scheduling problems lend themselves to easy descriptions. So in a few minutes you can describe the problem.
The research should be on a topic of significant interest and related to things I have worked on, and one in which I have some intuition about the direction of research and conjectures that might be true and provable with elementary methods.
I usually treat undergraduates the same way as PhD students, while being aware that they have limited time (a year) as opposed to PhD students who might begin a vaguely defined research project.
Have them work jointly with a PhD student, if the research is close enough to the PhD students interests and expertise. It’s also a valuable mentoring experience for the PhD student. Simply having a couple of undergrads work on a project jointly can be motivating for both.
One benefit of tackling hard problems at this stage is that there is no downside. If a student does not make progress, in the worst case they read a few papers and learn some new things. This allows us to work on problems with less pressure than second and third year graduate students are under.

Over the last 25 years, I have had the opportunity to work with a very large number of talented undergraduates –from University of Maryland (UMD) and Northwestern University, but also many via the NSF funded REU site program (REU CAAR) that Bill Gasarch (UMD) and I co-ran from 2012-2018. Many of the students I advised, have published the work they did and subsequently received fellowships and admission to top Ph.D programs. Recent graduates are Elissa Redmiles (Ph.D. UMD), Frederic Koehler (Ph.D. MIT) and Riley Murray (Ph.D. Caltech). I specifically wanted to mention An Zhu (Ph.D. Stanford University) who first opened my eyes to the amazing work that is possible by undergraduates.

About the Author Samir Khuller received his M.S and Ph.D from Cornell University in 1989 and 1990, respectively, under the supervision of Vijay Vazirani. He was the first Elizabeth Stevinson Iribe Chair for CS at the University of Maryland. As chair he led the development of the Brendan Iribe Center for Computer Science and Innovation, a project completed in March 2019. In March 2019, Khuller joined Northwestern University as the Peter and Adrienne Barris Chair for CS.

His research interests are in graph algorithms, discrete optimization, and computational geometry. He has published about 200 journal and conference papers, and several book chapters on these topics. He served on the ESA Steering Committee from 2012-2016 and chaired the 2019 MAPSP Scheduling Workshop, and served on the program committee’s of many top conferences. From 2018-2021 he was Chair of SIGACT. In 2020, he received the CRA-E Undergraduate Research Mentoring Award and in 2021 he was selected as a Fellow of EATCS.

He received the National Science Foundation’s Career Development Award, several Department Teaching Awards, the Dean’s Teaching Excellence Award and also a CTE-Lilly Teaching Fellowship. In 2003, he and his students were awarded the “Best newcomer paper” award for the ACM PODS Conference. He received the University of Maryland’s Distinguished Scholar Teacher Award in 2007, as well as a Google Research Award and an Amazon Research Award. In 2016, he received the European Symposium on Algorithms inaugural Test of Time Award for his work with Sudipto Guha on Connected Dominating Sets. He graduated at the top of the Computer Science Class from IIT-Kanpur.

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MSc and PhD Research Interests

Below is a listing of research areas represented in the Department of Computer Science. For some areas, their parent branch of Computer Science (such as Scientific Computing) is indicated in parentheses.

Artificial Intelligence (AI)

1. AI: Computational Linguistics & NLP

Research Topics: natural language processing (NLP), speech processing, information retrieval, machine translation, language acquisition, formal perspectives on language, cognitive modelling of language acquisition and processing, semantic change, lexical evolution, lexical composition, cross-linguistic semantic typology, applications of NLP in health and medicine, applications of NLP in the social sciences and humanities

2. AI: Computational Social Science

Research Topics: novel digital data and computational analyses for addressing societal challenges, analysis of online social networks and social media, intersection of AI and society, application of machine learning to social data, analysis of large-scale online data for social science applications, algorithmic fairness and bias

3. AI: Computer Vision

Research Topics: tracking, object recognition, 3D reconstruction, physics-based modelling of shape and appearance, computational photography, content-based image retrieval and human motion analysis

4. AI: Knowledge Representation and Reasoning

Research Topics: knowledge representation, reasoning and inference, planning and decision making, search, multi-agent systems, sequential decision-making, cognitive robotics , reasoning about knowledge, belief, acting and sensing, constraint and satisfiability reasoning

5. AI: Machine Learning

Research Topics:

Methods : deep learning, graphical models, reinforcement learning, stochastic optimization, approximate inference, structured prediction, representation learning

Theory : analysis of machine learning algorithms, convex and non-convex optimization methods, statistical learning theory

Focus in health : developing and applying machine learning methods that leverage the structure of data and problems in health including representation learning, reinforcement learning and inverse RL, prediction, risk stratification, and model interpretability

Focus in robotics : reinforcement learning, robot perception, learning and control, imitation learning, predictive models, exploration, lifelong learning, learning for self-driving cars

Focus in computer vision and graphics : image segmentation, detection

Focus in systems : cloud computing, operating systems, hardware acceleration for machine learning

6. AI: Robotics

Medical robotics, surgical robotics, continuum robotics, soft robots

Robot manipulation, kino-dynamic modelling of robots, motion planning, optimal control

Self-driving cars, mobile and field robotics, autonomous vehicles

Human-robot interaction, multi-agent systems

Computational Biology

7. Computational Biology

Research Topics: algorithms, machine learning, biomedical NLP, visualization for genomics, proteomics, and systems biology

Computational Medicine

8. Computational Medicine

Research Topics: machine learning, human computer interaction, vision, speech and NLP for healthcare and medicine, translating computational tools to the bedside, use of mobile devices in medicine, assistive technologies: design and deployment of enabling technology to be accessible to broader groups in society

Computer Graphics

9. Computer Graphics

Computational fabrication : 3D printing, laser cutting, geometric optimizations

Computational imaging : novel 3D sensors, computational cameras, modelling real-world light transport, computer vision for photography

Geometry processing : discrete differential geometry, surface acquisition

Animation : physics-based animation, character and facial animation, biomechanical simulation

Shape modeling : sketch-based modeling and rendering

Augmented and virtual reality : interaction, perception

Computer Science & Education

10. Computer Science & Education

Computer science education : teaching and learning of computer science. Examples include: introductory programming, advanced programming, software development, visual & end-user programming for non-computer scientists, computational thinking, fostering positive attitudes and motivating diverse learners in CS.

Using computer science to enhance education : using computer science techniques to investigate educational principles and design technology for learning. Examples include: human-computer interaction design of educational technologies, adaptive and personalized learning, crowdsourcing & human computation that involves learners and instructors, educational data mining, learning analytics, artificial intelligence and statistical machine learning in education (e.g. active learning, reinforcement learning for adaptive instruction), intelligent self-improving systems & intelligent tutoring systems, randomized A/B experimentation at scale, software learning, cognitive & interactive tutorials

Data Management Systems

11. Data Management Systems

Research Topics: query processing and optimization, web data management, video and image query processing systems, applications of machine learning to processing massive data sets, approximate techniques for query processing, spatial query processing, database system internals

Human-Computer Interaction (HCI)

12. Human-Computer Interaction

Computer-Supported Cooperative Learning (CSCL)

Computer-Supported Cooperative Work (CSCW), crowdsourcing, human computation, education/learning at scale, MOOCs, interactive tutorials, software learning

Information and Communication Technology and Development (ICTD) : analysis, design and development of computing technologies for sustainable development

Information visualization : visual analytics, perception & cognition, graphical design, interface design, interaction methods

UI technologies : input/output sensors and displays, interaction methods, ubiquitous computing, AR/VR, mobile and wearable computing, room scale computing

Critical computing : critical study of contemporary computing culture, design theory

Digital fabrication : methods, materials, tools

Human-robot interaction : interface design, modelling of robots and interfaces, shared autonomy, human-robot teamwork, user modelling, intent prediction

Programming Languages & Formal Methods

13. Programming Languages & Formal Methods

Research Topics: study of programming languages, language theory, program analysis (static and dynamic), program logics and proofs of program correctness, program synthesis (automated programming), automated verification, model checking, quantitative reasoning about software systems, software safety and security, theorem proving

Quantum Computing

14. Quantum Computing

Research Topics: algorithms, cryptography, complexity, verification of quantum computers, algorithms for near-term quantum computers, quantum hamiltonian complexity, quantum machine learning, optimization, applications to physics and chemistry

Scientific Computing (SC)

15. SC: Compilers for Scientific Applications

Research Topics: domain-specific compilers, code generation, programming languages for scientific computing, autotuning, verification of numerical codes

16. SC: High-Performance Computing

Research Topics: parallel algorithms, extreme-scale scientific computing, computational science, performance modelling, compilers for scientific computing

17. SC: Numerical Analysis and Computing

Research Topics: numerical methods and analysis of ODEs and PDEs, solution of large sparse linear systems, numerical software, high performance scientific computing, scientific visualization, computational finance, medical imaging, stochastic models, effective software for systems of ODEs, DDEs and related problems, sensitivity analysis of ODE solvers

Systems & Networks (SN)

18. SN: Computer Architecture

Research Topics: architecture, hardware, compiler optimization, hardware-based acceleration, high performance computing, energy-efficient computing, hardware/software cooperation, memory systems, hardware security

19. SN: Computer Networks

Research Topics: network protocols/algorithms/systems/architecture, software-defined networking, theory of networks, online social networks, wireless networks, data centre networks, rate control, quality of service and pricing

20. SN: Systems

Research Topics: operating systems, mobile/pervasive/ubiquitous computing, virtual machines, compiler optimization, file and storage systems, reliability, cloud computing, data-intensive computing, distributed systems, datacentres

Social Networks

21. Social Networks

Research Topics: algorithms for social network analysis, graph structure of social networks, user behavior and interaction, reputation and influence, content distribution and sharing, incentive mechanisms, game theory, optimal design of online social networks, network formation and dynamics, social networks and economic theory

Software Engineering

22. Software Engineering

Software modeling and reasoning : modelling and reasoning about software, including reasoning specifically about safety and security, product line analysis, analysis of change in requirements, designs and code, analysis in/for model-driven software development

Requirements engineering : analysis and modelling of software requirements, enterprise contexts and stakeholder dependencies

Social media and collaborative work : support for team collaboration and awareness, software as a service, open source communities and distributed software development

Sustainability Informatics

23. Sustainability Informatics

Research Topics: computational models of climate change, sustainability analytics, energy efficient computing, and green IT

Theoretical Computer Science

24. Theoretical Computer Science

Research Topics: general interest in theoretical computer science including areas 25-30

25. Theory: Algorithms

Research Topics: design and analysis of algorithms and data structures, continuous and discrete optimization, randomization, approximation, fairness, algorithmic aspects of social networks

26. Theory: Computational Complexity

Research Topics: complexity of boolean functions (including circuit complexity, algebraic circuits, and quantum complexity), proof complexity, communication complexity, classes and resources (time, space, randomness)

27. Theory: Cryptography and Foundations of Privacy

Research Topics: rigorous definitions of security, cryptographic algorithms and protocols, quantum cryptography, private data analysis

28. Theory: Game Theory and Social Choice

Research Topics: equilibrium analysis, voting, resource allocation, incentives in machine learning

29. Theory: Graph Theory and Graph Algorithms

30. Theory: Distributed Computing

Research Topics: algorithms and lower bounds for distributed computing problems

For enquiries call:

+1-469-442-0620

Programming

Latest Computer Science Research Topics for 2024

Home Blog Programming Latest Computer Science Research Topics for 2024

Everybody sees a dream—aspiring to become a doctor, astronaut, or anything that fits your imagination. If you were someone who had a keen interest in looking for answers and knowing the “why” behind things, you might be a good fit for research. Further, if this interest revolved around computers and tech, you would be an excellent computer researcher!

As a tech enthusiast, you must know how technology is making our life easy and comfortable. With a single click, Google can get you answers to your silliest query or let you know the best restaurants around you. Do you know what generates that answer? Want to learn about the science going on behind these gadgets and the internet?

For this, you will have to do a bit of research. Here we will learn about top computer science thesis topics and computer science thesis ideas.

Why is Research in Computer Science Important?

Computers and technology are becoming an integral part of our lives. We are dependent on them for most of our work. With the changing lifestyle and needs of the people, continuous research in this sector is required to ease human work. However, you need to be a certified researcher to contribute to the field of computers. You can check out Advance Computer Programming certification to learn and advance in the versatile language and get hands-on experience with all the topics of C# application development.

1. Innovation in Technology

Research in computer science contributes to technological advancement and innovations. We end up discovering new things and introducing them to the world. Through research, scientists and engineers can create new hardware, software, and algorithms that improve the functionality, performance, and usability of computers and other digital devices.

2. Problem-Solving Capabilities

From disease outbreaks to climate change, solving complex problems requires the use of advanced computer models and algorithms. Computer science research enables scholars to create methods and tools that can help in resolving these challenging issues in a blink of an eye.

3. Enhancing Human Life

Computer science research has the potential to significantly enhance human life in a variety of ways. For instance, researchers can produce educational software that enhances student learning or new healthcare technology that improves clinical results. If you wish to do Ph.D., these can become interesting computer science research topics for a PhD.

4. Security Assurance

As more sensitive data is being transmitted and kept online, security is our main concern. Computer science research is crucial for creating new security systems and tactics that defend against online threats.

1. Integrated Blockchain and Edge Computing Systems: A Survey, Some Research Issues, and Challenges

Welcome to the era of seamless connectivity and unparalleled efficiency! Blockchain and edge computing are two cutting-edge technologies that have the potential to revolutionize numerous sectors. Blockchain is a distributed ledger technology that is decentralized and offers a safe and transparent method of storing and transferring data.

As a young researcher, you can pave the way for a more secure, efficient, and scalable architecture that integrates blockchain and edge computing systems. So, let's roll up our sleeves and get ready to push the boundaries of technology with this exciting innovation!

Blockchain helps to reduce latency and boost speed. Edge computing, on the other hand, entails processing data close to the generation source, such as sensors and IoT devices. Integrating edge computing with blockchain technologies can help to achieve safer, more effective, and scalable architecture.

Moreover, this research title for computer science might open doors of opportunities for you in the financial sector.

2. A Survey on Edge Computing Systems and Tools

With the rise in population, the data is multiplying by manifolds each day. It's high time we find efficient technology to store it. However, more research is required for the same.

Say hello to the future of computing with edge computing! The edge computing system can store vast amounts of data to retrieve in the future. It also provides fast access to information in need. It maintains computing resources from the cloud and data centers while processing.

Edge computing systems bring processing power closer to the data source, resulting in faster and more efficient computing. But what tools are available to help us harness the power of edge computing?

As a part of this research, you will look at the newest edge computing tools and technologies to see how they can improve your computing experience. Here are some of the tools you might get familiar with upon completion of this research:

Apache NiFi: A framework for data processing that enables users to gather, transform, and transfer data from edge devices to cloud computing infrastructure.
Microsoft Azure IoT Edge: A platform in the cloud that enables the creation and deployment of cutting-edge intelligent applications.
OpenFog Consortium: An organization that supports the advancement of fog computing technologies and architectures is the OpenFog Consortium.

3. Machine Learning: Algorithms, Real-world Applications, and Research Directions

Machine learning is the superset of Artificial Intelligence; a ground-breaking technology used to train machines to mimic human action and work. ML is used in everything from virtual assistants to self-driving cars and is revolutionizing the way we interact with computers. But what is machine learning exactly, and what are some of its practical uses and future research directions?

To find answers to such questions, it can be a wonderful choice to pick from the pool of various computer science dissertation ideas.

You will discover how computers learn several actions without explicit programming and see how they perform beyond their current capabilities. However, to understand better, having some basic programming knowledge always helps. KnowledgeHut’s Programming course for beginners will help you learn the most in-demand programming languages and technologies with hands-on projects.

During the research, you will work on and study

Algorithm: Machine learning includes many algorithms, from decision trees to neural networks.
Applications in the Real-world: You can see the usage of ML in many places. It can early detect and diagnose diseases like cancer. It can detect fraud when you are making payments. You can also use it for personalized advertising.
Research Trend: The most recent developments in machine learning research, include explainable AI, reinforcement learning, and federated learning.

While a single research paper is not enough to bring the light on an entire domain as vast as machine learning; it can help you witness how applicable it is in numerous fields, like engineering, data science & analysis, business intelligence, and many more.

Whether you are a data scientist with years of experience or a curious tech enthusiast, machine learning is an intriguing and vital field that's influencing the direction of technology. So why not dig deeper?

4. Evolutionary Algorithms and their Applications to Engineering Problems

Imagine a system that can solve most of your complex queries. Are you interested to know how these systems work? It is because of some algorithms. But what are they, and how do they work? Evolutionary algorithms use genetic operators like mutation and crossover to build new generations of solutions rather than starting from scratch.

This research topic can be a choice of interest for someone who wants to learn more about algorithms and their vitality in engineering.

Evolutionary algorithms are transforming the way we approach engineering challenges by allowing us to explore enormous solution areas and optimize complex systems.

The possibilities are infinite as long as this technology is developed further. Get ready to explore the fascinating world of evolutionary algorithms and their applications in addressing engineering issues.

5. The Role of Big Data Analytics in the Industrial Internet of Things

Datasets can have answers to most of your questions. With good research and approach, analyzing this data can bring magical results. Welcome to the world of data-driven insights! Big Data Analytics is the transformative process of extracting valuable knowledge and patterns from vast and complex datasets, boosting innovation and informed decision-making.

This field allows you to transform the enormous amounts of data produced by IoT devices into insightful knowledge that has the potential to change how large-scale industries work. It's like having a crystal ball that can foretell.

Big data analytics is being utilized to address some of the most critical issues, from supply chain optimization to predictive maintenance. Using it, you can find patterns, spot abnormalities, and make data-driven decisions that increase effectiveness and lower costs for several industrial operations by analyzing data from sensors and other IoT devices.

The area is so vast that you'll need proper research to use and interpret all this information. Choose this as your computer research topic to discover big data analytics' most compelling applications and benefits. You will see that a significant portion of industrial IoT technology demands the study of interconnected systems, and there's nothing more suitable than extensive data analysis.

6. An Efficient Lightweight Integrated Blockchain (ELIB) Model for IoT Security and Privacy

Are you concerned about the security and privacy of your Internet of Things (IoT) devices? As more and more devices become connected, it is more important than ever to protect the security and privacy of data. If you are interested in cyber security and want to find new ways of strengthening it, this is the field for you.

ELIB is a cutting-edge solution that offers private and secure communication between IoT devices by fusing the strength of blockchain with lightweight cryptography. This architecture stores encrypted data on a distributed ledger so only parties with permission can access it.

But why is ELIB so practical and portable? ELIB uses lightweight cryptography to provide quick and effective communication between devices, unlike conventional blockchain models that need complicated and resource-intensive computations.

Due to its increasing vitality, it is gaining popularity as a research topic as someone aware that this framework works and helps reinstate data security is highly demanded in financial and banking.

7. Natural Language Processing Techniques to Reveal Human-Computer Interaction for Development Research Topics

Welcome to the world where machines decode the beauty of the human language. With natural language processing (NLP) techniques, we can analyze the interactions between humans and computers to reveal valuable insights for development research topics. It is also one of the most crucial PhD topics in computer science as NLP-based applications are gaining more and more traction.

Etymologically, natural language processing (NLP) is a potential technique that enables us to examine and comprehend natural language data, such as discussions between people and machines. Insights on user behaviour, preferences, and pain areas can be gleaned from these encounters utilizing NLP approaches.

But which specific areas should we leverage on using NLP methods? This is precisely what you’ll discover while doing this computer science research.

Gear up to learn more about the fascinating field of NLP and how it can change how we design and interact with technology, whether you are a UX designer, a data scientist, or just a curious tech lover and linguist.

8. All One Needs to Know About Fog Computing and Related Edge Computing Paradigms: A Complete Survey

If you are an IoT expert or a keen lover of the Internet of Things, you should leap and move forward to discovering Fog Computing. With the rise of connected devices and the Internet of Things (IoT), traditional cloud computing models are no longer enough. That's where fog computing and related edge computing paradigms come in.

Fog computing is a distributed approach that brings processing and data storage closer to the devices that generate and consume data by extending cloud computing to the network's edge.

As computing technologies are significantly used today, the area has become a hub for researchers to delve deeper into the underlying concepts and devise more and more fog computing frameworks. You can also contribute to and master this architecture by opting for this stand-out topic for your research.

Tips and Tricks to Write Computer Research Topics

Before starting to explore these hot research topics in computer science you may have to know about some tips and tricks that can easily help you.

Know your interest.
Choose the topic wisely.
Make proper research about the demand of the topic.
Get proper references.
Discuss with experts.

By following these tips and tricks, you can write a compelling and impactful computer research topic that contributes to the field's advancement and addresses important research gaps.

From machine learning and artificial intelligence to blockchain, edge computing, and big data analytics, numerous trending computer research topics exist to explore.

One of the most important trends is using cutting-edge technology to address current issues. For instance, new IIoT security and privacy opportunities are emerging by integrating blockchain and edge computing. Similarly, the application of natural language processing methods is assisting in revealing human-computer interaction and guiding the creation of new technologies.

Another trend is the growing emphasis on sustainability and moral considerations in technological development. Researchers are looking into how computer science might help in innovation.

With the latest developments and leveraging cutting-edge tools and techniques, researchers can make meaningful contributions to the field and help shape the future of technology. Going for Full-stack Developer online training will help you master the latest tools and technologies.

Frequently Asked Questions (FAQs)

Research in computer science is mainly focused on different niches. It can be theoretical or technical as well. It completely depends upon the candidate and his focused area. They may do research for inventing new algorithms or many more to get advanced responses in that field.

Yes, moreover it would be a very good opportunity for the candidate. Because computer science students may have a piece of knowledge about the topic previously. They may find Easy thesis topics for computer science to fulfill their research through KnowledgeHut.

There are several scopes available for computer science. A candidate can choose different subjects such as AI, database management, software design, graphics, and many more.

Ramulu Enugurthi

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A guide for early-career researchers in computational science

by Samuel Jarman, SciencePOD

In recent years, a growing number of students have embraced scientific computation as an integral component of their graduate research. Yet since many of them are new to the field, they often have little to no coding experience, or any prior knowledge of computational tools. For many students starting out in the field, this can seem daunting, and leaves them unsure of where to start.

In a new article published in The European Physical Journal Plus , a team led by Idil Ismail, a current graduate student at the University of Warwick, UK, present an introductory guide to the field for researchers embarking on new careers.

The team's work will help new graduate students to navigate the complexities of scientific computation science as they begin their journey in computational science research, and could ultimately help the wider field to become more transparent and inclusive.

Modern computational science is now being used in a wide array of subject areas: including mathematics, physics, chemistry, engineering, and the life sciences . Yet despite their many differences, these different branches of the field share many of the same techniques, which graduate students will need to learn regardless of the area they decide to pursue.

In their article, Ismail's team aim to highlight the universal skills, themes, and methods widely used by computational scientists. In nine carefully structured sections, they cover a broad spectrum of important techniques: including scientific programming, machine learning , and Bash scripting, With its approachable and instructive tone, the article is not intended as an exhaustive guide.

Instead, it acts as a useful starting point: signposting readers to more in-depth sources, and encouraging them to expand their knowledge by seeking out information for themselves. Altogether, the team's work will help early-career computational scientists to build a toolkit of indispensable skills, and will be a valuable resource for any graduate student entering the field.

Provided by SciencePOD

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51 Best Colleges for Computer Science – 2024

May 8, 2024

The CS major is exploding at colleges and universities across the United States and gaining admission at any of the best colleges for computer science is highly competitive. The computer science explosion extends even beyond the higher education world as more and more public k-12 systems are requiring that every student learns how to code. These trends are a recognition of the tech-heavy nature of modern industry as well as modern life in general. Attending any of the Best Colleges for Computer Science that cracked our list will set graduates up for a rewarding and lucrative tech career.

Methodology

Click here to read our methodology for the Best Colleges for Computer Science.

Salary Information

Want to know how much money graduates of the top CS schools make when they begin their careers? For each college listed (and hundreds of additional schools), you can view the starting salaries for computer science majors .

Best Colleges for Computer Science

Here’s a quick preview of the first ten computer science institutions that made our list. Detailed profiles and stats can be found when you scroll below.

1) Massachusetts Institute of Technology

2) Stanford University

3) California Institute of Technology

4) University of California, Berkeley

5) Columbia University

6) University of Michigan

7) Duke University

8) Harvey Mudd College

9) Georgia Institute of Technology

10) Princeton University

All of the schools profiled below have stellar reputations in the area of CS and commit substantial resources to undergraduate education. For each of the best computer science colleges, College Transitions will provide you with—when available—the university’s:

Cost of Attendance
Acceptance Rate
Median SAT
Median ACT
Retention Rate
Graduation Rate

We will also include a longer write-up of each college’s:

Academic Highlights – Includes facts like student-to-faculty ratio, average class size, number of majors offered, and most popular majors.
Professional Outcomes – Includes info on the rate of positive outcomes, companies employing alumni, and graduate school acceptances.

Massachusetts Institute of Technology

Cambridge, MA

Academic Highlights: Undergraduates pursue one of 57 majors and 59 minors at this world-class research institution that continues to be one of the world’s most magnetic destinations for math and science geniuses. The student-to-faculty ratio is an astonishing 3-to-1, and over two-fifths of all class sections have single-digit enrollments, and 70% of courses contain fewer than twenty students. The highest numbers of degrees conferred in 2022 were in the following majors: engineering (31%), computer science and engineering (28%), mathematics (10%), and the physical sciences (7%).

Professional Outcomes: The Class of 2023 saw 29% of its members enter the world of employment and 43% continue on their educational paths. The top employers included Accenture, Amazon, Microsoft, Goldman Sachs, Google, General Motors, the US Navy, Apple, Bain & Company, and McKinsey. The mean starting salary for an MIT bachelor’s degree holder was $95,000. The most frequently attended graduate schools are a who’s who of elite institutions including MIT itself, Stanford, Caltech, Harvard, and the University of Oxford.

Enrollment: 4,657
Cost of Attendance: $82,730
Median SAT: 1550
Median ACT: 35
Acceptance Rate: 4%
Retention Rate: 99%
Graduation Rate: 95%

Stanford University

Palo Alto, CA

Academic Highlights: Stanford has three undergraduate schools: the School of Humanities & Sciences, the School of Engineering, and the School of Earth, Energy, and Environmental Sciences. 69% of classes have fewer than twenty students, and 34% have a single-digit enrollment. Programs in engineering, computer science, physics, mathematics, international relations, and economics are arguably the best anywhere. In terms of sheer volume, the greatest number of degrees are conferred in the social sciences (17%), computer science (16%), engineering (15%), and interdisciplinary studies (13%).

Professional Outcomes: Stanford grads entering the working world flock to three major industries in equal distribution: business/finance/consulting/retail (19%); computer, IT (19%); and public policy and service, international affairs (19%). Among the companies employing the largest number of recent grads are Accenture, Apple, Bain, Cisco, Meta, Goldman Sachs, Google, McKinsey, Microsoft, and SpaceX. Other companies that employ hundreds of Cardinal alums include LinkedIn, Salesforce, and Airbnb. Starting salaries for Stanford grads are among the highest in the country.

Enrollment: 8,049 (undergraduate); 10,236 (graduate)
Cost of Attendance: $87,833
Median SAT: 1540
Retention Rate: 98%

California Institute of Technology

Pasadena, CA

Academic Highlights: Across all divisions, there are 28 distinct majors. Possessing an absurdly favorable 3:1 student-to-faculty ratio, plenty of individualized attention is up for grabs. Class sizes are not quite as tiny as the student-to-faculty ratio might suggest, but 70% of courses enroll fewer than twenty students, and 28% enroll fewer than ten. Computer science is the most popular major, accounting for 38% of all degrees conferred. Engineering (30%), the physical sciences (20%), and mathematics (6%) also have strong representation.

Professional Outcomes: Caltech is a rare school that sees six-figure average starting salaries for its graduates; in 2022, the median figure was $120,000. Forty-three percent of recent grads went directly into the workforce and found homes at tech giants such as Google, Intel, Microsoft, Apple, and Meta. A healthy 46% of those receiving their diplomas in 2022 continued directly on the higher education path, immediately entering graduate school. Ninety-seven percent of these students were admitted to one of their top-choice schools.

Enrollment: 982
Cost of Attendance: $86,886
Median SAT: Test Blind
Median ACT: Test Blind
Acceptance Rate: 3%
Graduation Rate: 94%

University of California, Berkeley

Berkeley, CA

Academic Highlights: More than 150 undergraduate majors and minors are available across six schools: the College of Letters and Science, the College of Chemistry, the College of Engineering, the College of Environmental Design, the College of Natural Resources, and the Haas School of Business. Many departments have top international reputations including computer science, engineering, chemistry, English, psychology, and economics. 22% of sections contain nine or fewer students, and over 55% of students assist faculty with a research project or complete a research methods course.

Professional Outcomes: Upon graduating, 49% of Cal’s Class of 2022 had already secured employment, and 20% were headed to graduate school. Business is the most popular sector, attracting 62% of employed grads; next up are industrial (17%), education (8%), and nonprofit work (7%). The median starting salary was $86,459 across all majors. Thousands of alumni can be found in the offices of Google, Apple, and Meta, and 500+ Golden Bears are currently employed by Oracle, Amazon, and Microsoft. The school is the number one all-time producer of Peace Corps volunteers.

Enrollment: 32,831 (undergraduate); 12,914 (graduate)
Cost of Attendance: $48,574 (in-state); $82,774 (out-of-state)
Acceptance Rate: 11%
Retention Rate: 96%

Columbia University

New York, NY

Academic Highlights: Columbia offers 100+ unique areas of undergraduate study as well as a number of pre-professional and accelerated graduate programs. Class sizes at Columbia are reasonably small and the student-to-faculty ratio is favorable; however, in 2022, it was revealed that the university had been submitting faulty data in this area. It is presently believed that 58% of undergraduate courses enroll 19 or fewer students. The greatest number of degrees are conferred in the social sciences (22%), computer science (15%), engineering (14%), and biology (7%).

Professional Outcomes: Examining the most recent graduates from Columbia College and the Fu Foundation School of Engineering & Applied Science, 73% had found employment within six months, and 20% had entered graduate school. The median starting salary for graduates of Columbia College/Columbia Engineering is above $80,000. Many graduates get hired by the likes of Amazon, Goldman Sachs, Morgan Stanley, Google, Citi, McKinsey, and Microsoft.

Enrollment: 8,832
Cost of Attendance: $89,587

University of Michigan

Ann Arbor, MI

Academic Highlights: There are 280+ undergraduate degree programs across fourteen schools and colleges, and the College of Literature, Science, and the Arts (LSA) enrolls the majority of students. The Ross School of Business offers highly rated programs in entrepreneurship, management, accounting, and finance. The College of Engineering is also one of the best in the country. By degrees conferred, engineering (15%), computer science (14%), and the social sciences (11%) are most popular. A solid 56% of classes have fewer than 20 students.

Professional Outcomes: Within three months of graduating, 89% of LSA grads are employed full-time or in graduate school, with healthcare, education, law, banking, research, nonprofit work, and consulting being the most popular sectors. Within three months, 99% of Ross grads are employed with a median salary of $90k. Top employers include Goldman Sachs, Deutsche Bank, EY, Morgan Stanley, PwC, Deloitte, and Amazon. Within six months, 96% of engineering grads are employed (average salary of $84k) or in grad school. General Motors, Ford, Google, Microsoft, Apple, and Meta employ the greatest number of alumni.

Enrollment: 32,695 (undergraduate); 18,530 (graduate)
Cost of Attendance: $35,450 (in-state); $76,294 (out-of-state)
Median SAT: 1470
Median ACT: 33
Acceptance Rate: 18%
Retention Rate: 97%
Graduation Rate: 93%

Duke University

Academic Highlights: The academic offerings at Duke include 53 majors, 52 minors, and 23 interdisciplinary certificates. Class sizes are on the small side—71% are nineteen or fewer, and almost one-quarter are less than ten. A stellar 5:1 student-to-faculty ratio helps keep classes so reasonable even while catering to five figures worth of graduate students. Computer Science is the most popular area of concentration (11%), followed by economics (10%), public policy (9%), biology (8%), and computer engineering (7%).

Professional Outcomes: At graduation, approximately 70% of Duke diploma-earners enter the world of work, 20% continue into graduate schools, and 2% start their own businesses. The industries that attract the largest percentage of Blue Devils are tech (21%), finance (15%), business (15%), healthcare (9%), and science/research (6%). Of the 20% headed into graduate school, a hefty 22% are attending medical school, 18% are in PhD programs, and 12% are entering law school. The med school acceptance rate is 85%, more than twice the national average.

Enrollment: 6,640
Cost of Attendance: $85,238
SAT Range: 1490-1570
ACT Range: 34-35
Acceptance Rate: 6%
Graduation Rate: 97%

Harvey Mudd College

Claremont, CA

Academic Highlights: While 62% of courses have an enrollment under 20, another 32% enroll between 20 and 39 students. Regardless, Mudd prides itself on offering graduate-level research opportunities and experiential learning to all undergrads. Only six majors are offered: biology, chemistry, computer science, engineering, mathematics, and physics. All are incredibly strong. Students also have the option to combine certain disciplines into what amounts to a double major.

Professional Outcomes: Seventy-two percent of the Class of 2022 planned on entering a job right after receiving their bachelor’s degree. The highest number of recent Harvey Mudd graduates are scooped up by the following companies (in order of representation): Meta, Microsoft, and Caltech. Graduates average an impressive $117,500 starting salary, a phenomenal number even when accounting for the preponderance of STEM majors. Many Harvey Mudd grads—20% in 2022—go directly into graduate school programs.

Enrollment: 906
Cost of Attendance: $89,115
Median SAT: 1530
Acceptance Rate: 13%
Graduation Rate: 92%

Georgia Institute of Technology

Atlanta, GA

Academic Highlights: Georgia Tech’s engineering and computer science programs are at the top of any “best programs” list. Being a large research university, the student-to-faculty ratio is a less-than-ideal 22:1, leading to some larger undergraduate class sections. In fact, 49% of courses had enrollments of more than thirty students in 2022-23. On the other end of the spectrum, 8% of sections had single-digit enrollments. In terms of total number of degrees conferred, the most popular areas of study are engineering (51%), computer science (21%), and business (9%).

Professional Outcomes: More than three-quarters of recent grads had already procured employment by the time they were handed their diplomas. You will find graduates at every major technology company in the world. The median salary reported by that group was $80,000. Many remain on campus to earn advanced engineering degrees through Georgia Tech, but the school’s reputation is such that gaining admission into other top programs including MIT, Carnegie Mellon, Berkeley, Stanford, and Caltech.

Enrollment: 18,416
Cost of Attendance: $29,950 (In-State); $52,120 (Out-of-State)
Acceptance Rate: 17%

Princeton University

Princeton, NJ

Academic Highlights: 39 majors are available at Princeton. Just under three-quarters of class sections have an enrollment of 19 or fewer students, and 31% have fewer than ten students. Princeton is known for its commitment to undergraduate teaching, and students consistently rate professors as accessible and helpful. The Engineering Department is widely recognized as one of the country’s best, as is the School of Public and International Affairs.

Professional Highlights: Over 95% of a typical Tiger class finds their next destination within six months of graduating. Large numbers of recent grads flock to the fields of business and engineering, health/science, & tech. Companies presently employing hundreds of Tiger alumni include Google, Goldman Sachs, Microsoft, McKinsey & Company, Morgan Stanley, IBM, and Meta. The average salary ranges from $40k (education, health care, or social services) to $100k (computer/mathematical positions). Between 15-20% of graduating Tigers head directly to graduate/professional school.

Enrollment: 5,604 (undergraduate); 3,238 (graduate)
Cost of Attendance: $86,700
Graduation Rate: 98%

University of California, San Diego

San Diego, CA

Academic Highlights: There are 140+ undergraduate majors offered at UCSD, and all students join one of eight undergraduate colleges meant to forge flourishing communities within the larger university. Biology has the highest representation of all majors (19%) followed by engineering (12%), the social sciences (11%), and computer science (9%). UCSD’s computer science and engineering programs have stellar reputations in the corporate and tech communities, and programs in biology, economics, and political science are among the best anywhere.

Professional Outcomes: Employers of recent graduates included the Walt Disney Company, Tesla, NBC Universal, PwC, Northrop Grumman, and EY. More than 1,000 current Google employees are UC San Diego alumni, and Qualcomm, Amazon, and Apple all employ 500+ each. The median early career salary is $65,000 across all majors, placing the university in the top 10 public universities in the country. UCSD also fares well in measures of its return-on-investment potential.

Enrollment: 33,096 (undergraduate); 8,386 (graduate)
Cost of Attendance: $31,830 (in-state); $64,404 (out-of-state)
Acceptance Rate: 25%
Retention Rate: 93%
Graduation Rate: 88%

University of California, Los Angeles

Los Angeles, CA

Academic Highlights: UCLA offers 125 majors in 100+ academic departments, and more than 60 majors require a capstone experience that results in the creation of a tangible product under the mentorship of faculty members. The most commonly conferred degrees are in the social sciences (25%), biology (16%), psychology (11%), mathematics (8%), and engineering (7%). Departmental rankings are high across the board, especially in computer science, engineering, film, fine and performing arts, mathematics, and political science.

Professional Outcomes: UCLA grads flow most heavily into the research, finance, computer science, and engineering sectors. High numbers of recent grads can be found at Disney, Google, EY, Teach for America, Amazon, and Oracle. Hundreds also can be found at Bloomberg, Deloitte, Mattel, Oracle, and SpaceX. The average starting salary exceeds $55,000. 16% of recent grads enrolled directly in a graduate/professional school, with other CA-based institutions like Stanford, Pepperdine, USC, Berkeley, and Loyola Marymount being the most popular.

Enrollment: 33,040 (undergraduate); 15,010 (graduate)
Cost of Attendance: $38,517 (in-state); $71,091 (out-of-state)
Acceptance Rate: 9%

Harvard University

Academic Highlights: There are 50 undergraduate fields of study referred to as concentrations; many are interdisciplinary. Even with a graduate population of over 14,000 to cater to, undergraduate class sizes still tend to be small, with 42% of sections having single-digit enrollments and 71% being capped at nineteen. Economics, government, and computer science are the three most popular areas of concentration at Harvard. Biology, chemistry, physics, math, statistics, sociology, history, English, and psychology all sit atop most departmental ranking lists.

Professional Outcomes: The Crimson Class of 2022 saw 15% of students head directly into graduate/professional school. Of the graduates entering the world of work (virtually everyone else), 58% were entering either the consulting, finance, or technology field. Over 1,000 Harvard alumni presently work for Google and over 500 for Microsoft, McKinsey & Company, and Goldman Sachs. Turning our attention to those moving on to graduate school, Harvard grads with at least a 3.5 GPA typically enjoy acceptance rates into medical school of 90% or greater.

Enrollment: 7,240
Cost of Attendance: $79,450

Cornell University

Academic Highlights: A diverse array of academic programs includes 80 majors and 120 minors spread across the university’s seven schools/colleges. Classes are a bit larger at Cornell than at many other elite institutions. Still, 55% of sections have fewer than 20 students. Most degrees conferred in 2022 were in computer science (17%), engineering (13%), business (13%), and biology (13%). The SC Johnson College of Business houses two undergraduate schools, both of which have phenomenal reputations.

Professional Outcomes: Breaking down the graduates of the College of Arts and Sciences, the largest school at Cornell, 68% entered the workforce, 28% entered graduate school, 1% pursued other endeavors such as travel or volunteer work, and the remaining 3% were still seeking employment six months after receiving their diplomas. The top sectors attracting campus-wide graduateswere financial services (18%), technology (17%), consulting (15%), and education (10%). Of the students from A&S going on to graduate school, 15% were pursuing JDs, 5% MDs, and 22% PhDs.

Enrollment: 15,735
Cost of Attendance: $88,150
Median SAT: 1520
Median ACT: 34
Acceptance Rate: 7%

University of Southern California

Academic Highlights : There are 140 undergraduate majors and minors within the Dornsife College of Arts & Sciences alone, the university’s oldest and largest school. The Marshall School of Business, Viterbi School of Engineering, and programs in communication, the cinematic arts, and the performing arts are highly acclaimed. Popular areas of study are business (22%), social sciences (11%), visual and performing arts (11%), communications/journalism (9%), and engineering (8%). Most courses enroll 10-19 students, and USC does an excellent job facilitating undergraduate research opportunities.

Professional Outcomes: 96% of undergrads experience positive postgraduation outcomes within six months of earning their degree. The top five industries entered were finance, consulting, advertising, software development, and engineering; the median salary across all majors is an astounding $79k. Presently, between 300 and 1,500 alumni are employed at each of Google, Amazon, Apple, Microsoft, KPMG, Goldman Sachs, and Meta. Graduate/professional schools enrolling the greatest number of 2022 USC grads include NYU, Georgetown, Harvard, Stanford, Pepperdine, and UCLA.

Enrollment: 20,699 (undergraduate); 28,246 (graduate)
Cost of Attendance: $90,921
Median SAT: 1510
Acceptance Rate: 12%

Brown University

Providence, RI

Academic Highlights: Students must choose one of 80+ “concentration programs,” but there are no required courses. Class sizes tend to be small—68% have fewer than twenty students—and 35% are comprised of nine or fewer students. Biology, economics, computer science, mathematics, and engineering are among the most popular areas of concentration at Brown; however, it is hard to distinguish any one program, because Brown possesses outstanding offerings across so many disciplines.

Professional Outcomes: Soon after receiving their Brown diplomas, 69% of graduates enter the world of employment. Companies employing the greatest number of Brown alums include Google, Microsoft, Goldman Sachs, Amazon, Morgan Stanley, Apple, McKinsey & Company, and Bain & Company. The Class of 2022 saw 27% of graduates go directly into graduate/professional school. Right out of undergrad, Brown students boasted an exceptional 81% admission rate to med school and an 81% admission rate to law school.

Enrollment: 7,639
Cost of Attendance: $84,828
Acceptance Rate: 5%
Graduation Rate: 96%

Carnegie Mellon University

Pittsburgh, PA

Academic Highlights: There are a combined 80+ undergraduate majors and 90 minors available across the six schools. Impressively, particularly for a school with more graduate students than undergrads, CMU boasts a 6:1 student-to-faculty ratio and small class sizes, with 36% containing single digits. In a given school year, 800+ undergraduates conduct research through the University Research Office. The most commonly conferred degrees are in engineering (21%), computer science (16%), mathematics (12%), business (10%), and visual and performing arts (9%).

Professional Outcomes: By the end of the calendar year in which they received their diplomas, 66% of 2022 grads were employed, and 28% were continuing to graduate school. The companies that have routinely scooped up CMU grads include Google, Meta, Microsoft, Apple, Accenture, McKinsey, and Deloitte. With an average starting salary of $105,194, CMU grads outpace the average starting salary for a college grad nationally. Of those pursuing graduate education, around 20% typically enroll immediately in PhD programs.

Enrollment: 7,509
Cost of Attendance: $84,412

Swarthmore College

Swarthmore, PA

Academic Highlights: Swarthmore offers forty undergraduate programs and runs 600+ courses each academic year. Small, seminar-style courses are the norm—an outstanding 33% of sections enroll fewer than ten students, and 70% contain a maximum of nineteen students. Social science degrees are the most commonly conferred, accounting for 24% of all 2022 graduates. Future businessmen/women, engineers, and techies are also well-positioned, given Swat’s incredibly strong offerings in economics, engineering, and computer science.

Professional Outcomes: 68% of Class of 2022 grads entered the workforce shortly after graduation. Popular industries included education (17%), consulting (16%), and financial services (13%); the median starting salary was $60,000. Google is a leading employer of Swarthmore grads followed by Amazon, Goldman Sachs, IBM, and a number of the top universities. 18% of 2022 grads pursued advanced degrees, with 35% pursuing a PhD, 35% entering master’s programs, 10% heading to law school, and 7% matriculating into medical school.

Enrollment: 1,625
Cost of Attendance: $81,376
Median SAT: 1500

The University of Texas at Austin

Academic Highlights: UT Austin offers over 150 majors, including those at the Cockrell School of Engineering, one of the most heralded undergraduate engineering schools around, and The McCombs School of Business, which dominates in the specialty areas of accounting and marketing. The computer science department is also top-ranked. In terms of degrees conferred, engineering is tied with biology (12%) followed by communication (11%), business (11%), and the social sciences (8%). The elite Plan II Honors Program is one of the best in the country.

Professional Outcomes: Within the College of Liberal Arts, six months after graduating, 68% of Longhorns are employed and 24% have entered graduate school. The for-profit sector attracts 65% of those employed while 19% enter public sector employment and 16% pursue jobs at a nonprofit. Major corporations that employ more than 500 UT Austin grads include Google, Meta, Oracle, Microsoft, IBM, and Apple. Engineering majors took home a median income of $79k and business majors took home $70k.

Enrollment: 41,309 (undergraduate); 11,075 (graduate)
Cost of Attendance: $30,752-$34,174 (in-state); $61,180-$69,310 (out-of-state)
Median SAT: 1430
Median ACT: 32
Acceptance Rate: 31%
Retention Rate: 95%

University of California, Irvine

Academic Highlights: UCI offers eighty undergrad programs as well as many opportunities for personal connection; 56% of all sections enroll 19 or fewer students and over 60% of students conduct a research project. The most commonly conferred degrees are the social sciences (16%), business (12%), psychology (11%), and biology (9%). The Samueli School of Engineering has a solid reputation as does the Bren School, the only independent computer science school in the UC system. Programs in public health and biological sciences earn very high marks.

Professional Outcomes: Accounting, aerospace, internet and software, K-12 education, real estate, and retail are among the industries attracting the greatest number of Anteaters. Companies employing large numbers of recent grads include Boeing, the Walt Disney Company, Google, EY, and Microsoft. Hundreds of alumni are also found at Kaiser Permanente, Meta, Apple, Edwards Lifesciences, and Deloitte. The median salary is $69,000, with CS grads earning close to $120k right off the bat. UCI has a very strong reputation for premed.

Enrollment: 28,661 (undergraduate); 7,275 (graduate)
Cost of Attendance: $40,202 (in-state); $72,776 (out-of-state)
Acceptance Rate: 26%
Retention Rate: 91%
Graduation Rate: 87%

Williams College

Williamstown, MA

Academic Highlights: The school’s 25 academic departments offer 36 majors and a number of concentrations rather than minors. An unparalleled 40% of courses have fewer than ten students enrolled; the median class size is 12 students. Programs in economics, English, history, math, and political science are especially renowned, and the greatest number of degrees are conferred in the social sciences (26%), the physical sciences (10%), math and statistics (9%), psychology (9%), and computer science (7%).

Professional Outcomes: Among the Class of 2022, 92% were employed or continuing their educational journey within six months of graduating. Business and education typically attract the most students, with popular companies/organizations including Apple, Google, Goldman Sachs, The New York Times Co., the Peace Corps, and Teach for America. The median annual income for 2022 grads was $75,000. 75% pursue an advanced degree within five years of leaving Williams, with the most frequently attended graduate programs being Harvard, Columbia, and Yale.

Enrollment: 2,152 (undergraduate); 53 (graduate)
Cost of Attendance: $81,160
Acceptance Rate: 8%

Yale University

New Haven, CT

Academic Highlights: Yale offers 80 majors, most of which require a one- to two-semester senior capstone experience. Undergraduate research is a staple, and over 70% of classes—of which there are over 2,000 to choose from—have an enrollment of fewer than 20 students, making Yale a perfect environment for teaching and learning. Among the top departments are biology, economics, global affairs, engineering, history, and computer science. The social sciences (26%), biology (11%), mathematics (8%), and computer science (8%) are the most popular areas of concentration.

Professional Outcomes: Shortly after graduating, 73% of the Yale Class of 2022 had entered the world of employment and 18% matriculated into graduate programs. Hundreds of Yale alums can be found at each of the world’s top companies including Google, Goldman Sachs, McKinsey & Company, Morgan Stanley, and Microsoft. The most common industries entered by the newly hired were finance (20%), research/education (16%), technology (14%), and consulting (12%). The mean starting salary for last year’s grads was $81,769 ($120k for CS majors). Nearly one-fifth of students immediately pursue graduate school.

Enrollment: 6,590 (undergraduate); 5,344 (graduate)
Cost of Attendance: $87,705

Johns Hopkins University

Baltimore, MD

Academic Highlights: With 53 majors as well as 51 minors, JHU excels in everything from its bread-and-butter medical-related majors to international relations and dance. Boasting an enviable 6:1 student-to-faculty ratio and with 78% of course sections possessing an enrollment under 20, face time with professors is a reality. Many departments carry a high level of clout, including biomedical engineering, chemistry, English, and international studies. Biology, neuroscience, and computer science, which happen to be the three most popular majors, can also be found at the top of the national rankings.

Professional Outcomes: The Class of 2022 saw 94% of graduates successfully land at their next destination within six months of exiting the university; 66% of graduates entered the world of employment and a robust 19% went directly to graduate/professional school. The median starting salary across all majors was $80,000 for the Class of 2022. JHU itself is the most popular choice for graduate school. The next most frequently attended institutions included Columbia, Harvard, Yale, and MIT.

Enrollment: 6,044
Cost of Attendance: $86,065

University of Illinois at Urbana-Champaign

Champaign-Urbana, IL

Academic Highlights: Eight of UIUC’s fifteen schools cater to undergraduate students. There are 150 academic programs offered, including those at the acclaimed Grainger College of Engineering and Gies College of Business. In sheer volume of degrees conferred, engineering and business/marketing are tied at 19%, followed by the social sciences (9%) and psychology (6%). 39% of sections are capped at 19 students. 29% of undergraduates work with a faculty member on a research project; another 22% have some type of fieldwork, practicum, or clinical experience.

Professional Outcomes: 95% of the members of the Class of 2022 landed at their next destination within six months of graduation, with 38% matriculating directly into an advanced degree program. 57% were employed full-time; the most popular sectors were finance, consulting, healthcare, electronics, and education. Corporations landing the most recent Illini grads were KPMG, Deloitte, Epic Systems, EY, PwC, and Amazon. The average salary across all Class of 2022 majors was an extremely solid $75,000.

Enrollment: 35,120 (undergraduate); 21,796 (graduate)
Cost of Attendance: $35,926-$41,190 (in-state); $55,386-$63,290 (out-of-state)
Median SAT: 1440
Acceptance Rate: 79%
Graduation Rate: 85%

University of Pennsylvania

Philadelphia, PA

Academic Highlights : 90 distinct degrees are available across four schools: the College of Arts & Sciences, the College of Applied Science and Engineering, the College of Nursing, and the world-renowned Wharton School. The greatest number of students pursue degrees in business (19%), social sciences (14%), biology (11%), health sciences (9%), engineering (9%), and computer science (9%). The university boasts an exceptional 26% of courses with an enrollment under ten and 59% with an enrollment under twenty as well as multiple ways for undergrads to conduct research.

Professional Outcomes: 75% of Class of 2022 grads were employed within six months of graduating, and 18% were in graduate school. Finance attracted the highest percentage of grads (30%) followed by consulting (20%), technology (15%), and healthcare (10%). Employers hiring the greatest number of 2022 grads included JPMorgan, Boston Consulting Group, McKinsey, Bain & Company, Meta, and Goldman Sachs. The median starting salary for all graduates is $80,000. For those continuing their educational journeys, the most popular move is to remain at Penn, followed by Columbia and Harvard.

Enrollment: 9,760 (undergraduate); 13,614 (graduate)
Cost of Attendance: $89,028

University of Washington – Seattle

Seattle, WA

Academic Highlights: 180+ undergraduate majors are offered across thirteen colleges/schools. Personal connections with professors abound as 55% of grads complete a faculty-mentored research project. The College of Engineering, which includes the College of Computer Science & Engineering, is one of the best in the nation; UW also boasts strong programs in everything from business to social work to environmental science. The most popular degrees are the social sciences (13%), biology (12%), computer science (11%), and business (8%).

Professional Outcomes: Within months of graduation, 73% of Class of 2022 grads were employed and 17% were continuing their education. The most popular employers of the Class of 2022 included Google, Amazon, Microsoft, Boeing, and KPMG. Across all living alumni, 6,000+ work for Microsoft, and 4000+ work for each of Boeing and Amazon. Of those headed to graduate/professional school, just over half remain in state, mostly at UW itself. Large numbers of 2022 grads also headed to Columbia, Johns Hopkins, and USC.

Enrollment: 36,872 (undergraduate); 16,211 (graduate)
Cost of Attendance: $34,554 (in-state); $63,906 (out-of-state)
Median SAT: 1420
Acceptance Rate: 48%
Retention Rate: 94%
Graduation Rate: 84%

University of Maryland, College Park

College Park, MD

Academic Highlights: Undergraduates can select from 100+ majors across twelve colleges. 18% of degrees are conferred in computer science, followed by the social sciences (13%), with criminology, government and politics, and economics being the most popular majors. Engineering (13%), business (11%), and biology (8%) are next in line. The School of Business, the School of Engineering, and the College of Journalism are all top-ranked, as are programs in computer science and criminology. 46% of sections enroll fewer than twenty students.

Professional Outcomes: Within six months of graduating, 96% of Class of 2022 grads had positive outcomes. 67% found employment; the companies/organizations that hired the greatest number of grads included Northrop Grumman, Deloitte, Amazon, and EY. Meta, Apple, and Google employ more than 200 alumni each. The mid-50% salary range for 2022 grads was $55k-$83k. 21% of the Class of 2022 headed directly to graduate and professional school; 11% entered doctoral programs, 5% entered medical school, and 5% entered law school.

Enrollment: 30,353 (undergraduate); 10,439 (graduate)
Cost of Attendance: $31,540 (in-state); $60,918 (out-of-state)
Acceptance Rate: 84%
Graduation Rate: 89%

University of Chicago

Chicago, IL

Academic Highlights: There are 53 majors at UChicago, but close to half of all degrees conferred are in four majors: economics, biology, mathematics, and political science, all of which have particularly sterling reputations. Economics alone is the selection of roughly one-fifth of the undergraduate population. Over 75% of undergrad sections have an enrollment of nineteen or fewer students, and undergraduate research opportunities are ubiquitous as 80% of students end up working in a research capacity alongside a faculty member.

Professional Outcomes: On commencement day, 99% of the Class of 2023 were employed or continuing their education. Business and financial services (30%) and STEM (12%) were the two sectors that scooped up the most graduates, but public policy and consulting were also well-represented. The most popular employers of recent grads include Google, JPMorgan, Goldman Sachs, McKinsey & Company, Bank of America, Citi, and Accenture. For those heading to grad school, the top seven destinations are Yale, Columbia, Penn, MIT, Stanford, UCLA, and Johns Hopkins.

Enrollment: 7,653 (undergraduate); 10,870 (graduate)
Cost of Attendance: $89,040

University of Texas at Dallas

Academic Highlights: There are 140+ degree plans at UT Dallas which sports a 25:1 student-to-faculty ratio. Only 7% of classes are taught by graduate assistants, but classes are on the large side – 27% of course sections contain 50 or more students. The two most popular areas of study at this university are business (20%) and computer science (20%). Biology (14%), engineering (13%), and health professions (8%) also enjoy solid popularity. Even better, UT Dallas has a strong national reputation in all of these academic areas.

Professional Outcomes: The most commonly entered industries are internet and software, healthcare, accounting, IT, and higher education. Those graduating with a degree in information technology and systems had an average starting salary of $76,900 while those earning an accounting degree brought home a mean figure of $59,700. UT Dallas graduates have less undergraduate debt than the national average and receive the third-best ROI of any public university in Texas.

Enrollment: 21,617
Cost of Attendance: $35,960 (In-State); $51,126
Median SAT: 1290
Median ACT: 28
Acceptance Rate: 85%
Retention Rate: 87%
Graduation Rate: 74%

Dartmouth College

Hanover, NH

Academic Highlights: Dartmouth sports 60+ majors and a stunning breadth of course selections for an institution of its size. The learning environment at Dartmouth is extraordinarily intimate. Not only do 61% of course sections have under twenty students, but 18% have single-digit enrollments. The student-to-faculty ratio is an outstanding 7:1. Top programs offered by Big Green include biology, economics, neuroscience, and government. The social sciences are the most popular, accounting for 32% of degrees conferred, followed by computer science (10%), mathematics (9%), engineering (9%), and biology (7%).

Professional Outcomes: A great reputation along with a passionate alumni network that is 80,000 strong leads Dartmouth grads to successful transitions into graduate school and the world of work. Included in the top ten employers of Dartmouth grads are a number of investment banks including Goldman Sachs, Morgan Stanley, Bain & Company, Citibank, and Deutsche Bank. Right off the bat, 52% of graduates make more than $70,000 in salary. Those pursuing graduate degrees often flock to the likes of Harvard, Columbia, and Princeton.

Enrollment: 4,458
Cost of Attendance: $87,793

Amherst College

Amherst, MA

Academic Highlights: A 7:1 student-to-faculty ratio allows for 66% of courses to have fewer than twenty students and 32% to have single-digit enrollments. By senior year, 98% of seniors report feeling close enough to a faculty member to ask for a letter of recommendation. Amherst possesses strong offerings across the board, most notably in economics, English, history, mathematics, and law The social sciences account for 22% of degrees conferred, while 14% are in mathematics, 11% in biology, and 7% in computer science

Professional Outcomes: Six months after graduation, 93% of the Class of 2022 had already found its way into the world of employment, graduate school, or a volunteer organization. The largest employers of Amherst grads includes Google, Deloitte, Morgan Stanley, and Goldman Sachs. The schools where the highest number of Amherst grads can be found pursuing advanced degrees include MIT, Dartmouth, and the University of Pennsylvania. Fifty to sixty Amherst grads apply to medical school each year, and the acceptance rate hovers around 75-80%.

Enrollment: 1,898
Cost of Attendance: $84,840

New York University

Academic Highlights: NYU is divided into a number of smaller (but still quite large) colleges organized by discipline; in sum, there are 230 areas of undergraduate study across nine schools and colleges. For its size, a commendable 58% of classes have an enrollment under 20 students. While all schools within NYU have solid reputations, Stern holds the distinction as one of the top undergraduate business programs in the country. For those entering film, dance, drama, or other performing arts, Tisch is as prestigious a place as you can find to study.

Professional Outcomes: Within six months of exiting, 94% of Class of 2022 grads had landed at their next destination, with 78% employed and 21% in graduate school. The top industries for employment were healthcare (11%), internet and software (9%), finance (8%), and entertainment (8%). Large numbers of alumni can be found at Google, Deloitte, Morgan Stanley, Goldman Sachs, IBM, JP Morgan Chase, Citi, and Amazon. The mean starting salary is $75,336. In 2022, business, arts and sciences, and law school were the most popular grad school destinations.

Enrollment: 29,401 (undergraduate); 29,711 (graduate)
Cost of Attendance: $90,222-$96,172

University of California, Santa Barbara

Santa Barbara, CA

Academic Highlights: There are 90 undergraduate majors across three schools: the College of Letters and Science, the College of Engineering, and the College of Creative Studies. The social sciences are the most popular area of study, accounting for 27% of the total degrees conferred. Biology (10%), math (9%), and psychology (9%) are next in popularity. The school has highly regarded programs in communication, computer science, engineering, physics, environmental science, and the performing arts. More than half of sections contain fewer than 20 students, and 72% enroll 29 or fewer.

Professional Outcomes: Within six months of earning their diplomas, 84% of grads had found employment. The most popular industries were science/research (16%), engineering/computer programming (14%), business (13%), finance/accounting (11%), and sales (10%). Top employers of recent grads include Google, EY, KPMG, Oracle, Amazon, IBM, and Adobe. Many alumni also can be found at Apple, Meta, Microsoft, and Salesforce. Two years after graduating, UCSB alumni make an average salary of $55k; more than half make $100k by mid-career.

Enrollment: 23,460 (undergraduate); 2,961 (graduate)
Cost of Attendance: $41,289 (in-state); $73,863 (out-of-state)
Acceptance Rate: 28%
Retention Rate: 92%
Graduation Rate: 86%

Washington University in St. Louis

St. Louis, MO

Academic Highlights : WashU admits students into five schools, many of which offer nationally recognized programs: Arts & Sciences, the Olin School of Business, the School of Engineering & Applied Sciences, and the Art of Architecture programs housed within the Sam Fox School of Design and Visual Arts. The most commonly conferred degrees are in engineering (13%), social sciences (13%), business (13%), biology (11%), and psychology (10%). 66% of classes have fewer than 20 students, and over one-quarter have single-digit enrollments. 65% double major or pursue a minor.

Professional Outcomes: The Class of 2022 sent 52% of grads into the workforce and 28% into graduate and professional schools. Companies employing the highest number of WashU grads feature sought-after employers such as Amazon, Bain, Boeing, Deloitte, Google, IBM, Goldman Sachs, and Microsoft. Of the employed members of the Class of 2022 who reported their starting salaries, 79% made more than $60k. The universities welcoming the largest number of Bears included the prestigious institutions of Caltech, Columbia, Harvard, Penn, Princeton, and Stanford.

Enrollment: 8,132 (undergraduate); 8,880 (graduate)
Cost of Attendance: $83,760

University of Wisconsin – Madison

Madison, WI

Academic Highlights: There are 230+ undergraduate majors offered across eight schools and colleges, including the top-ranked School of Business and College of Engineering as well as the College of Letters and Science, the College of Agricultural and Life Sciences, and the Schools of Nursing, Education, Pharmacy, and Human Ecology. Undergrads can expect a mix of large and small classes, with 44% of sections enrolling fewer than 20 students. Business (18%), biology (12%), the social sciences (11%), and engineering (10%) are most popular.

Professional Outcomes: In a recent year, 46% of job-seeking grads graduated with an offer. Top employers included UW-Madison, Epic, Kohl’s, Oracle, Deloitte, and UW Health. Across all graduating years, companies employing 250+ alumni include Google, Target, Microsoft, Amazon, Apple, PwC, Accenture, and Meta. 28% of recent grads enrolled directly in graduate/professional school; the majority stayed at UW–Madison while others headed to Columbia, Northwestern, and Carnegie Mellon. The university is the top producer of Peace Corps volunteers.

Enrollment: 37,230 (undergraduate); 12,656 (graduate)
Cost of Attendance: $28,916 (in-state); $58,912 (out-of-state)
Median ACT: 30
Acceptance Rate: 49%

Carleton College

Northfield, MN

Academic Highlights: Students work closely with their professors, and the college is routinely rated atop lists of best undergraduate teaching institutions. Small classes are the norm with the average being only sixteen students. It offers 33 majors, the most popular of which are within the disciplines of the social sciences (19%), the physical sciences (14%), biology (11%), computer science (11%), mathematics (10%), and psychology (8%).

Professional Outcomes: Target, Epic Systems, Google, Wells Fargo, and Amazon all employ large numbers of graduates. Carleton is a breeding ground for future scholars as a ridiculously high number of graduates go on to earn PhDs. In fact, by percentage, Carleton is one of the top five producers in the country of future PhDs. They produce an incredible number of doctoral degree holders in the areas of economics, math, political science, sociology, chemistry, physics, biology, and history.

Enrollment: 2,034
Cost of Attendance: $82,167
Median SAT: 1490
Graduation Rate: 91%

Northwestern University

Evanston, IL

Academic Highlights : Northwestern is home to six undergraduate schools, including Medill, which is widely regarded as one of the country’s best journalism schools. The McCormick School of Engineering also achieves top rankings, along with programs in economics, social policy, and theatre. The social sciences account for the greatest number of degrees conferred (19%), followed by communications/journalism (13%), and engineering (11%). 45% of classes have nine or fewer students enrolled; 78% have fewer than twenty enrollees. 57% of recent grads had the chance to conduct undergraduate research.

Professional Outcomes: Six months after graduating, 69% of the Class of 2022 had found employment and 27% were in graduate school. The four most popular professional fields were consulting (18%), engineering (18%), business/finance (16%), and communications/marketing/media (13%). Employers included the BBC, NBC News, The Washington Post , NPR, Boeing, Google, IBM, Deloitte, PepsiCo, Northrop Grumman, and Goldman Sachs. Across all majors, the average starting salary was $73k. Of those headed straight to graduate school, engineering, medicine, and business were the three most popular areas of concentration.

Enrollment: 8,659 (undergraduate); 14,073 (graduate)
Cost of Attendance: $91,290

Worcester Polytechnic Institute

Worcester, MA

Academic Highlights: Worcester Polytechnic Institute (WPI) offers a hands-on and innovative project-based curriculum; all students complete a minimum of two long-term research projects that are focused on solving real-world problems. A staggering 52% of its classes enroll fewer than ten students, creating an incredible level of academic intimacy. The most popular majors are under the engineering umbrella (63%) and computer science (16%). The undergraduate engineering program is respected worldwide and frequently graces lists of top schools.

Professional Outcomes: Within six months of graduating, 94% of 2022 grads landed jobs or enrolled full-time in graduate school. Recent grads found jobs at top companies including Airbnb, DraftKings, Amazon Robotics, and NASA. Hundreds of WPI alumni are employed at Raytheon, Pratt & Whitney, Dell, and BAE Systems. The average starting salary is over $74,000 and is one of the highest in the country. Over one-quarter of grads elect to pursue an advanced degree immediately after graduation, enrolling at institutions that recently included Georgia Tech, Brown, Johns Hopkins, and Stanford.

Enrollment: 5,246 (undergraduate); 2,062 (graduate)
Cost of Attendance: $81,751
Acceptance Rate: 57%

Pomona College

Academic Highlights: There are 48 majors and minors to select from with the most popular being social sciences (23%), biology (13%), and computer science (12%). Majors in economics, international relations, chemistry, and mathematics receive especially high marks. More than 600 courses are on the menu at Pomona alone, but students can access any of the Claremont Consortium’s 2,700 courses. Pomona’s 8:1 student-to-teacher ratio leads to an average class size of only 15 students, and over 50% of the undergraduate population conduct research alongside a faculty member.

Professional Outcomes: 71% of the Class of 2022 were employed within six months of graduating. Overall, the largest number of alumni can be found at Google, Kaiser Permanente, Microsoft, Amazon, and Meta. Recently, economics degree-earners have landed jobs at Goldman Sachs, Wells Fargo, Morgan Stanley, or Accenture. Majors in the hard sciences frequently landed at top research laboratories and hospitals. Of the 21% of 2022 grads who were accepted directly into graduate school, the most frequently attended institutions included the University of Cambridge, Duke, Harvard, Caltech, UChicago, and Stanford.

Enrollment: 1,761
Cost of Attendance: $88,296

University of Virginia

Charlottesville, VA

Academic Highlights: Undergrads can study within one of seven colleges/schools, which all offer many small classes; 15% boast single-digit enrollment and 48% contain 19 or fewer students. The McIntire School of Commerce and the School of Engineering and Applied Science have glowing reputations. Other notable strengths include computer science, economics, and political philosophy, policy, and law. The most popular degree areas are liberal arts/general studies (22%), the social sciences (14%), engineering (11%), business/marketing (8%), and biology (7%).

Professional Outcomes: Upon receiving their degree, 95% of the Class of 2022 immediately joined the workforce–with an average starting salary of $90k–or headed directly to graduate school. The most popular industries were internet & software, higher education, and management consulting. Capital One (85), Deloitte (46), Amazon (38), and Bain & Co. (26) scooped up the greatest number of 2022 grads. UVA itself was the most popular grad school destination followed by Columbia, Virginia Commonwealth University, and Johns Hopkins.

Enrollment: 17,496 (undergraduate); 8,653 (graduate)
Cost of Attendance: $39,494-49,874 (in-state); $78,214-90,378 (out-of-state)
Acceptance Rate: 19%

Northeastern University

Academic Highlights: Northeastern offers 290 majors and 180 combined majors within nine colleges and programs. Experiential learning is had by virtually all graduates, thanks to the school’s illustrious and robust co-op program. The D’Amore-McKim School of Business is a top-ranked school and offers one of the best international business programs anywhere, and both the College of Engineering and College of Computer Science are highly respected as well. Criminal justice, architecture, and nursing are three other majors that rate near the top nationally.

Professional Outcomes: Nine months after leaving Northeastern, 97% of students have landed at their next employment or graduate school destination. Huskies entering the job market are quickly rounded up by the likes of State Street, Fidelity Investments, IBM, and Amazon, all of whom employ 500+ Northeastern alums. Between 200 and 500 employees at Wayfair, Google, Amazon, Oracle, IBM, and Apple have an NU lineage. Starting salaries are above average (55% make more than $60k), in part due to the stellar co-op program.

Enrollment: 20,980 (undergraduate); 15,826 (graduate)
Cost of Attendance: $86,821

Purdue University — West Lafayette

West Lafayette, IN

Academic Highlights: Purdue offers over 200 majors at ten discipline-specific colleges, and 38% of course sections have an enrollment of 19 or fewer. Engineering and engineering technologies majors earn 34% of the degrees conferred by the university; the College of Engineering cracks the top ten on almost every list of best engineering schools. The Krannert School of Management is also well-regarded by employers; 11% of degrees conferred are in business. Other popular majors include computer science (10%) and agriculture (5%)—both are incredibly strong.

Professional Outcomes: Shortly after receiving their diplomas, 70% of 2022 grads headed to the world of employment while 24% headed to graduate/professional school. The top industries entered by grads in recent years are (1) health care, pharmaceuticals, and medical devices; (2) finance, insurance, and consulting; (3) manufacturing and machinery; (4) airline, aviation, and aerospace. Companies employing the greatest number of recent alumni were Amazon, Deloitte, PepsiCo, Labcorp, Lockheed Martin, and Microsoft. The average starting salary was $68k across all degree programs.

Enrollment: 37,949 (undergraduate); 12,935 (graduate)
Cost of Attendance: $22,812 (in-state); $41,614 (out-of-state)
Median SAT: 1330
Median ACT: 31
Acceptance Rate: 53%

Rutgers University — New Brunswick

New Brunswick, NJ

Academic Highlights: Rutgers is divided into 17 schools and colleges, collectively offering 100+ undergraduate majors. 41% of class sections have an enrollment of nineteen or fewer students. The greatest number of degrees are conferred in business (20%), computer science (12%), engineering (10%), health professions (10%), biology (9%), and social sciences (7%). Rutgers Business School sends many majors to top Wall Street investment banks, and programs in computer science, public health, and criminal justice have a terrific national reputation.

Professional Outcomes: Upon graduation, 82% of Class of 2022 grads had secured a first job or were heading to an advanced degree program. 67% headed directly to the world of employment, where the companies hiring the largest number of grads included Amazon, Johnson & Johnson, L’Oréal, and JP Morgan Chase. Investment banks like Goldman Sachs and Citi also employ hundreds of alumni, as do companies like Verizon, Bristol-Meyers Squibb, Novartis, Pfizer, and Google. The median starting salary across all majors was $70,000.

Enrollment: 36,344 (undergraduate); 14,293 (graduate)
Cost of Attendance: $37,849 (in-state); $57,138 (out-of-state)
Median SAT: 1370
Acceptance Rate: 66%

Virginia Polytechnic Institute and State University

Blacksburg, VA

Academic Highlights : Eight undergraduate colleges that offer 110+ distinct bachelor’s degrees are housed within Virginia Tech. 33% of sections contain fewer than 20 students, and 21% of recent graduates report participating in some type of undergraduate research experience. Engineering is the area where the greatest number of degrees are conferred (23%), but business (20%) is a close second. Both disciplines are among the most respected at Tech, along with computer science. Other popular majors include the family and consumer sciences (8%), social sciences (8%), biology (8%), and agriculture (4%).

Professional Outcomes: Within six months of graduating, 56% of the Class of 2022 were employed and 18% were in graduate school. One recent class sent large numbers to major corporations that included Deloitte (67), KPMG (44), Lockheed Martin (39), Capital One (30), EY (28), Booz Allen Hamilton (18), and Northrop Grumman (12). The median salary for 2022 graduates was $67,000. Among recent grads who decided to pursue an advanced degree, the greatest number stayed at VT, while others enrolled at Virginia Commonwealth University, George Mason University, William & Mary, Columbia, Duke, and Georgia Tech.

Enrollment: 30,434 (undergraduate); 7,736 (graduate)
Cost of Attendance: $37,252 (in-state); $58,750 (out-of-state)
Median ACT: 29

University of Minnesota–Twin Cities

Minneapolis, MN

Academic Highlights: There are 150 majors available across eight freshman-admitting undergraduate colleges. 65% of class sections enroll 29 or fewer students. The most commonly conferred degrees are in biology (13%), business & marketing (11%), engineering (10%), the social sciences (10%), computer science (9%), and psychology (8%). The College of Science and Engineering and the Carlson School of Management have strong national reputations, and the chemistry, economics, psychology, and political science departments are also well-regarded.

Professional Outcomes: The top seven companies snatching up the largest number of recent grads are all companies headquartered in the state of Minnesota: Medtronic, Target, 3M, United Health Group, US Bank, and Cargill. Google, Apple, and Meta all employ hundreds of Twin Cities alumni. The mean starting salary for recent grads was $50k. With 130 graduate programs in science, art, engineering, agriculture, medicine, and the humanities, the University of Minnesota retains many of its graduates as they pursue their next degrees.

Enrollment: 39,248 (undergraduate); 15,707 (graduate)
Cost of Attendance: $33,032-$35,632 (in-state); $54,446-$57,046
Acceptance Rate: 75%
Retention Rate: 90%

Pennsylvania State University — University Park

State College, PA

Academic Highlights: Penn State offers 275 majors and a number of top-ranked programs in a host of disciplines. The College of Engineering is rated exceptionally well on a national scale and is also the most popular field of study, accounting for 15% of the degrees conferred. The Smeal College of Business is equally well-regarded, earning high rankings in everything from supply chain management to accounting to marketing. It attracts 15% of total degree-seekers. 61% of classes have an enrollment below thirty students.

Professional Outcomes: By graduation, 70% of Nittany Lions have found their next employment or graduate school home. 98% of College of Business grads are successful within three months of exiting, flocking in large numbers to stellar finance, accounting, consulting, and technology firms. Hundreds of alumni work at Citi, Salesforce, and Meta, and more than 500 currently work at each of IBM, Deloitte, PwC, Amazon, EY, JPMorgan Chase, Microsoft, Google, and Oracle. 75% of 2022 grads employed full-time earned starting salaries greater than $50k.

Enrollment: 41,745 (undergraduate); 7,020 (graduate)
Cost of Attendance: $32,656 (in-state); $52,610 (out-of-state)
Median SAT: 1300
Acceptance Rate: 55%

University of Massachusetts Amherst

Academic Highlights: 110 majors are offered across eight undergraduate colleges, including the highly ranked Isenberg School of Management. Programs in sports management, architecture, computer science, and nursing are top-rated. Of all degrees conferred in 2022, business/marketing diplomas accounted for 14%, followed by biology (11%), social sciences (10%), psychology (8%), health professions (7%), engineering (7%), and computer science (7%). 47% of courses enroll fewer than 20 students, and 30% engage in undergraduate research.

Professional Outcomes: Six months after graduating, 65% of newly minted 2022 grads were employed full-time and 26% were attending graduate school part-time. The most populated industries are health/medical professions (13%), internet & software (10%), biotech & life sciences (4%), and higher education (4%). Companies presently employing 100+ Minutemen and Minutewomen include Oracle, Mass Mutual, Amazon, IBM, Google, Intel, Microsoft, PwC, Wayfair, and Apple. Boston is the most popular landing spot for graduates.

Enrollment: 23,936 (undergraduate); 7,874 (graduate)
Cost of Attendance: $37,219 (in-state); $59,896 (out-of-state)
Median SAT: 1380
Acceptance Rate: 58%
Graduation Rate: 83%

University of Colorado Boulder

Boulder, CO

Academic Highlights: CU Boulder offers 90 bachelor’s degree programs across seven different schools and colleges; the College of Engineering & Applied Science and the Leeds School of Business both possess excellent national reputations. Business/marketing is the discipline where the greatest number of degrees (15%) were conferred in 2022. Engineering (13%), biology (12%), social sciences (12%), and journalism (10%) are next in popularity. 41% of classes have fewer than 20 students, and only 19% of courses enroll 50 or more students.

Professional Outcomes : Within six months of leaving CU Boulder, 91% of recent grads were working or in graduate school. Those employed earned an estimated median salary of $54k, with the greatest number working at Lockheed Martin, Ball Aerospace, Deloitte, Qualcomm, Northrop Grumman, KPMG, Charles Schwab, and Boeing. More than 100 alumni can also be found at Google, Oracle, Amazon, Apple, and Microsoft. 20% of new grads immediately jumped into an advanced degree program, and 80% were accepted into their first-choice school.

Enrollment: 31,103 (undergraduate); 7,110 (graduate)
Cost of Attendance: $31,744 (in-state); $60,118 (out-of-state)
Median SAT: 1280
Retention Rate: 88%
Graduation Rate: 75%

Texas A&M University — College Station

College Station, TX

Academic Highlights: With nineteen schools and colleges and 130+ undergraduate degree programs, Texas A&M is a massive operation. As the name implies, there is a heavy emphasis on agriculture, engineering, and business, which all place well in national rankings and garner deep respect from major corporations and graduate/professional schools. Class sizes trend large, but 24% of courses enroll fewer than 20 students and personal connections with professors are entirely possible, particularly through the research-oriented LAUNCH program.

Professional Outcomes: On graduation day, 54% of students had already received at least one job offer and 22% were heading to graduate/professional school. Many Aggies go on to work at major oil, tech, and consulting firms; more than 500 are employed at each of ExxonMobil, Halliburton, Chevron, EY, Amazon, Microsoft, Intel, Accenture, and PWC. Starting salaries were strong—on average, College of Engineering grads made $80k and College of Agriculture & Life Sciences grads netted $54k. A&M is also the eighth-largest producer of law students in the entire country.

Enrollment: 57,512 (undergraduate); 16,502 (graduate)
Cost of Attendance: $31,058 (in-state); $59,336 (out-of-state)
Median SAT: 1270
Acceptance Rate: 63%

Stony Brook University (SUNY)

Stony Brook, NY

Academic Highlights: Stony Brook offers 60+ majors and 80+ minors across six undergraduate colleges. 38% of all sections contain nineteen or fewer students. A popular and locally well-regarded nursing program leads to the largest number of degrees being conferred in health professions (14%). Strong majors in biology (14%), math (10%), business (9%), engineering (7%), and computer sciences (6%) also draw many students. The school’s reputation in the hard sciences, particularly math, chemistry, and biomedical engineering, is aided by the affiliated Stony Brook University Hospital.

Professional Outcomes: Within two years of graduation, 61% of Stony Brook graduates are employed, and 34% have entered graduate/professional school. The organizations and companies employing the greatest number of Seawolves are Northwell Health, JPMorgan Chase, Google, Amazon, Citi, Morgan Stanley, Microsoft, Apple, Bloomberg, and Microsoft. Among those pursuing further education, common choices include Stony Brook itself, other SUNY or CUNY institutions, and NYC-based powerhouses like Columbia, Fordham, and NYU.

Enrollment: 17,509 (undergraduate); 8,201 (graduate)
Cost of Attendance: $33,008 (in-state); $52,798 (out-of-state)
Median SAT: 1410
Graduation Rate: 78%

The Ohio State University — Columbus

Columbus, OH

Academic Highlights: There are 200+ undergraduate majors and 18 schools and colleges housed within OSU. Business sees the greatest percentage of degrees conferred at 18% followed by engineering (15%), health professions (10%), and the social sciences (9%). It makes sense that so many flock to the business and engineering schools as they are among the highest-rated undergraduate programs in their respective disciplines. 40% of sections enroll fewer than 20 students, and approximately 20% of students gain research experience.

Professional Outcomes: Upon receiving their diplomas, 56% of Class of 2022 graduates were entering the world of employment while 17% were already accepted into graduate or professional school. Hordes of Buckeyes can be found at many of the nation’s leading companies. More than 2,000 alumni work for JPMorgan Chase, more than 1,000 are employed by Amazon, and more than 600 work for Google and Microsoft. Of the grads who directly matriculate into graduate or professional school, many continue in one of OSU’s own programs.

Enrollment: 45,728 (undergraduate); 14,318 (graduate)
Cost of Attendance: $27,241 (in-state); $52,747 (out-of-state)
Median SAT: 1340-1450
Median ACT: 29-32

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Computer Science Degree: What Your Career Can Look Like

The broad scope of the computer science degree allows you to open the door to endless possibilities within the field of technology. Many of the most dynamic and future-forward careers require candidates to have a strong background in computer science, making this one of the most valuable degree programs of our time.

Is Computer Science a Good Major?

So, is computer science a good major? The answer is a resounding “yes.” A computer science degree will prepare you to work in a wide range of computer and technology occupations. According to the U.S. Bureau of Labor Statistics (BLS), employment in this field is expected to grow at a much faster rate than average when compared to all other occupations, with about 377,500 job openings anticipated each year between now and 2032.

Ultimately, those interested in technology and computer science will find that this degree program prepares them for a long, lucrative , and engaging career.

Demand for Computer Science Professionals

In the digital era, nearly every industry has been significantly impacted by advancing technology, which has heightened the demand for computer science professionals.

These are some of the computer science occupations currently in high demand :

Computer and Information Research Scientists — 23% job growth rate
Information Security Analysts — 32% job growth rate
Web Developers — 16% job growth rate
Software Developers — 25% job growth rate

Growth Trends in Tech Industries

The technology sector is considered to be one of the strongest and most resilient sectors in the economy, and per reports from LinkedIn , these growth trends are driving the computer science industry forward:

Increased demand for specialized technology professionals, highlighting the importance of developing a niche skill set.
Increased hiring in the tech start-up sector, showcasing the strength of the computer science and technology industry overall.
Increased salary levels for most technology positions, highlighting the earning potential within this field.
Increased availability of remote positions, showcasing the flexibility available within this industry.

Salary Comparison With Other Majors

Given the fact that technology jobs are in high demand across all sectors, it’s not surprising that many of these positions pay higher than their non-tech counterparts.

The median annual salary in this field is about $100,000, and some of the highest-paying computer and information technology positions include:

Computer and Information Research Scientists — $136,000 median annual salary
Computer Network Architects — $126,000 median annual salary
Software Developers — $124,000 median annual salary
Database Administrators and Architects — $112,000 median annual salary
Information Security Analysts — $112,000 median annual salary

Flexibility and Versatility of Skills

The computer science degree program allows you to become proficient in a wide range of technology skills, which can prepare you for many of the top careers in the computer science and information technology fields. Many of these skills are flexible, transferable skills applicable in a wide range of settings, allowing you to customize your career path and apply your education in new and innovative ways.

Opportunities for Remote Work and Freelancing

Remote work has long been possible in the computer science and information technology sector, and in the last several years, the number of remote work opportunities has increased exponentially. Given the fact that most technology jobs can be done on the cloud, it’s not surprising that many tech professionals can work remotely and achieve a better sense of work-life balance when compared to other professions.

The Worth of a Computer Science Degree

While a computer science degree can prepare you for some of the highest-paying jobs in the technology sector, it’s important to keep in mind that the value of this degree extends far beyond salary. Many graduates find that a computer science degree allows them to pursue job opportunities that are interesting , as well as personally and professionally rewarding, making this one of the most worthwhile degrees to pursue those interested in the field of technology.

Cost of Education vs. Long-Term Benefits

Any degree program requires a significant financial investment, and a computer science degree is no exception. However, you will find that the cost of your education is a worthwhile investment, as a computer science degree prepares you for some of the most lucrative career opportunities of our time. You will find that this degree program prepares you for entry-level positions in computer science that offer significant growth potential, allowing you to embark on a long and rewarding career.

Continuous Learning and Skill Enhancement

While your computer science degree program provides you with a future-forward look at this dynamic industry, it’s important to be aware that change is guaranteed within the technology sector. Throughout your career, you will be able to build upon the foundation that you developed throughout your degree program and take advantage of continuous learning opportunities that will allow you to develop the latest, industry-specific skills required in most technology jobs.

Impact on Job Satisfaction and Fulfillment

The American Journal of Business Education notes that 60% of all college graduates, across all majors, report that they are highly satisfied with their jobs. However, within the computer science field, more than 67% of all graduates report that they are highly satisfied. Those who graduate with a computer science degree can combine their passion for technology with a specialized skill set, allowing them to pursue some of the most lucrative and rewarding positions in the current economy.

Recognition of Contribution to Technological Advancements

Regardless of the position that you pursue, if you work in the computer science industry, you will find that you take an active role in the advancements that will continue to drive our world forward. Recognition of this contribution can be very powerful and rewarding, allowing you to feel more satisfied and fulfilled in your job.

Exploring 4 Career Trajectories in Computer Science

There are a few different paths that you can take within the realm of the computer science field. You can specialize in one of these four common career paths:

1. Software Development and Engineering

Software development and engineering is a subset of computer science that focuses on computer programs. Software developers and engineers rely on the Software Development Life Cycle, or SDLC, to develop new and innovative software programs. Some of the top positions in software development and engineering include computer programmer, quality assurance engineer, software engineer , and database administrator.

2. Data Science and Analytics

In our data-driven age, there is heightened demand for both data scientists and data analytics professionals. There are distinct differences between these two career fields. Data scientists frequently work with machine learning algorithms and predictive modeling processes to make predictions about the future based on the data that has been harvested today. Data analytics professionals, on the other hand, work with structured data to provide businesses across all sectors with the data-driven solutions that they need to thrive in today’s complex economy.

3. Cybersecurity and Information Assurance

In a world where most business is conducted online, and digital transactions have become the norm, cybersecurity has never been more important. The field of cybersecurity focuses not only on mitigating cyberattacks but also preventing them. Some of the top positions in the field of cybersecurity include cybersecurity engineer, penetration tester, information security analyst , and incident responder.

4. Artificial Intelligence and Machine Learning

Artificial intelligence and machine learning are two of the most talked about topics in the technology sector, and these advanced technologies are significantly altering our daily lives. Within the field of artificial intelligence and machine learning, there are many career opportunities for graduates with a computer science degree. Some of the top jobs in artificial intelligence and machine learning include machine learning engineer, artificial intelligence engineer, data scientist, data engineer, robotics developer, and engineer.

Is a Computer Science Degree Worth It? Find Out at Carson-Newman University

Ready to kickstart your journey into the dynamic world of computer science? Explore the Computer Science program at Carson-Newman today to gain the skills and knowledge needed for a thriving career in technology. Take the first step toward your future success and apply now to join our innovative community of learners!

Carson-Newman University is a Christian university proud to offer dynamic, skills-based degree programs in a Christ-centered environment.

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