A list of the research interests of all the Computer Science professors at MIT:
Computational complexity, quantum computing.
Artificial intelligence, scientific computation, educational computing, societal and legal frameworks for information technology.
Program analysis and optimization, computer architecture.
Architecture synthesis and verification, digital design, term rewriting systems and lambda calculus. Parallel architectures and programming languages.
Computer networks, mobile and sensor computing systems, distributed systems.
Natural language processing.
Natural language processing: computer models of language acquisition and parsing. Computational biology and evolutionary theory including evolution of language. Artificial intelligence: formal models of learning, including inductive inference and computational complexity analysis of language. Cognitive science: word learning, semantics of natural languages.
Natural language processing and machine learning.
Theory of computation. The interdisciplinary fields of algorithmic game theory, computational biology, social networks and applied probability.
Artificial intelligence, intelligent multimodal interfaces and natural interaction; intellectual property issues in software.
Algorithms and data structures. Discrete and computational geometry. Combinatorial games.
Parallel computer system design to support functional languages and advanced environments for modular programming. Study of architecture, performance and reliability issues.
Image generation and creation; realistic rendering, real-time graphics, perceptually-based algorithms, non-photorealistic rendering, image-based rendering and editing, digital photography.
Machine learning applied to computer vision and computer graphics. Bayesian belief propagation and its generalizations. Bayesian models of visual perception.
Computational and systems biology, computational functional genomics. Expression of scientific models in computational form. Machine learning.
Cryptography, pseudo randomness, property testing, computational number theory, multi-party computations.
Computer vision, medical image analysis, medical image processing, image guided surgery, activity recognition.
Computational imaging, machine vision. Representation of objects and space. Photogrammetry.
Computational geometry, especially in high-dimensional spaces; databases and information retrieval; learning theory; design and analysis of algorithms; streaming and sketching algorithms.
Statistical inference and machine learning. Applications to computational biology and information retrieval. Artificial intelligence.
Software design and specification; design methods, tools and analysis; dependability; safety-critical systems; reverse engineering; static analysis, model checking, programming languages.
Computer systems: operating systems, networking, programming languages, compilers, and computer architecture for distributed systems, mobile systems and parallel systems.
Behavior learning, visually-guided map learning for mobile robots, planning in very large stochastic domains, learning relational models.
Information retrieval and digital libraries; analysis of algorithms, especially for graphs and optimization problems; applications of randomization; parallel algorithms.
Computer networks and data communication. Congestion control, network measurements, scalability and robustness of communications systems. Differentiated services, internet pricing, routing, content distribution, self-configurable and wireless networks and network security.
Artificial intelligence; robotics and computer vision.
Theory of distributed and real-time computing: mathematical models, specification, algorithm and system design, performance and fault-tolerance analysis. Distributed data management, communication, synchronization. Languages and tools for abstract distributed programming. Hybrid (continuous/discrete) systems. Mobile wireless networks.
Databases and computer systems; query processing, distributed systems, management of streaming data, adaptive data processing, sensor networking.
Software education environments. Semantics of programming languages, logic of programs, concurrent programs, lambda calculus.
Human-computer interfaces, intelligent interfaces, programming by demonstration, end-user programming languages, usability, software engineering, usability and security.
Artificial intelligence. Robotics and machine vision. Representation of knowledge and structure of personality. Common sense reasoning, theories of emotion and consciousness.
The design of an easy-to-control data networking infrastructure designed to bring about a new level of flexibility to network configuration. The Resilient Overlay Networks Project. Grid routing protocols.
Organization of large complex systems, artificial intelligence.
Program analysis, compilers, distributed computing, software engineering.
Sublinear time algorithms, randomized algorithms, computational complexity theory.
Robotics, mobile computing and information access.
Programming systems with a focus on software synthesis. Programming tools for parallel and high performance computing.
Database systems, query processing, data warehouses, federated databases, data visualization.
Complexity of finding ‘approximate’ solutions to combinatorial optimization problems; interplay of algebra with computer science and coding theory.
Artificial intelligence: learning, problem solving and programming. Computational performance models for intelligent behavior, especially modeling the behavior of engineers. Numerical models of physical systems.
Application of artificial intelligence techniques to medical decision making. Effective representation of knowledge. Personal health information systems, medical confidentiality.
Machine learning and robotics, including reinforcement learning, optimal control, legged robots, flapping-wing flight, nonlinear control theory, biological motor control, and computational neuroscience. Particular emphasis on solving difficult robotic control problems through a close coupling of mechanical design and learning control.
Autonomous robotics for mobility and manipulation; situational awareness through sensing and inference; location-based infrastructure and applications; assistive technology for health care.
Computer vision, machine learning and human perception; development of computer vision systems and solving real world recognition tasks; modeling human perceptual and cognitive capabilities; object recognition, classification of whole scenes; visual recognition and classification of places and objects.
Computer architecture and operating systems.
Artificial intelligence and computational theories of human intelligence, with special emphasis on the roles of language, vision and analogical reasoning.
Building practical secure systems. Operating systems, hardware design, networking, and distributing systems. Programming languages and tools, security analysis and verification.