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=A0

 

MASSACHUSETTS INSTITUTE OF TECHNOLOGY

Electrical Engineering and Computer Science=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0= =A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0= =A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0 July, 2003

 

=A0

GUIDE TO GRADUATE STUDY IN AREA II (COMPUTER = SCIENCE)

for students who started on or after September, = 1999

 

=A0

Graduate study in computer science at MIT is centered in Area II of the = Department of Electrical Engineering and Computer Science.=A0 This memorandum offers a brief road map of the Computer Science = graduate program in EECS.

 

This memorandum applies to students entering the Ph.D. program in September = 1999 or later.=A0 This includes = students who completed their M. Eng. degrees before September 1999 but did not begin = the rest of their PhD program before September 1999.

 

1. Computer = Science Programs

 

Academic programs for graduate students in the field of computer science lead to = the Master of Engineering, Master of Science, Engineer, and either Doctor of Philosophy or Doctor of

Science degree.=A0 These programs are = meant to prepare students for industrial, educational, governmental, and research positions.=A0 Either the Master = of Science degree or the Master of Engineering degree (or an equivalent) is = required for the Doctoral degree programs.

 

A thesis based on original work is required for each of the degrees in = computer science.=A0 For detailed = information on degree requirements consult the Departmental Memoranda 3903 (Master's = program) and 3800new (Doctoral program), available from the EECS Graduate = Office.=A0 The requirements can be briefly = summarized as follows:

 

=B7        Complete a Technical Qualifying Examination (TQE) and a Research Qualifying = Examination (RQE); see below for details.

 

=B7        Complete the requirements for a Master's degree.

 

=B7        Complete a minor program consisting of two subjects approved by the student's = Doctoral Committee.

 

=B7        Complete any additional subjects (up to two) required by the Doctoral = Committee.

 

=B7        Carry out a teaching assignment as approved by the Doctoral = Committee.

 

=B7        Write and present a thesis proposal to the Thesis = Committee.

 

=B7        Complete a doctoral thesis.

 

Several of the requirements require approval of the student's Doctoral = Committee.=A0 Ideally, this is the student's = Thesis Committee, composed of a Ph.D. thesis supervisor and at least two Ph.D. = thesis readers.=A0 Students are = encouraged to form thesis committees as early as they can, preferably by the time of = the RQE.=A0 If a thesis committee = does not exist by the time of the RQE, then the RQE committee (with input from = the faculty counselor) will evaluate the student's courses, = plans

for a minor, and plans for a teaching assignment at the time of the = RQE.=A0 Also, if a thesis committee does = not exist by the term following the RQE, then the department will appoint a = temporary doctoral committee.

 

Computer science is a rapidly evolving field, and much of its knowledge and = discipline is best acquired by direct involvement in research.=A0 Active research apprenticeship at an early stage is = regarded as a vital part of the graduate program of every student, and early = affiliation with an appropriate research group is important.=A0 For a list of faculty and research staff that supervise graduate research see Section 5.

 

2. = Examinations

 

As part of the Doctoral program, every student must complete two formal examinations.

 

The Technical Qualifying = Examination (TQE) requires students to demonstrate competence in three different = groups.=A0 Students should complete all = components of the TQE by the end of their second year in residence.=A0 See below for more details.

 

The objective of the Research = Qualifying Examination (RQE) is to monitor students' research progress as well = as skills in presentation, both written and oral.=A0 Students should aim to complete the RQE by then end of their = second year in residence.=A0 See below for = more details.

 

For more information on examinations, refer to Departmental memorandum = 3800new on the Doctoral program and to the memoranda 3805 Technical Qualifying = Examination and 3806 Research Qualifying Examination available from the Area II = website http://theory.lcs.mit.edu/areaii or the EECS = Graduate Office.

 

2.1 The TQE in = Area II

 

The TQE requires that a student demonstrate competence in four advanced = courses, selecting at least one course from each of the three groups (see Table below).=A0 Competence in each = course can be demonstrated by earning at least an A- grade.=A0 If a student gets two or more grades less than A-, an = oral examination will be required on all courses for which the grade is less = than A-.=A0 Each course grade less = than a B- also requires an oral examination in that course.=A0=A0

 

=A0

=A0

=A0

 

 

=A0

=A0

 

GROUP I:

SYSTEMS

 

 

 

6.821

 

6.824 = or 6.829

 

6.823 = or 6.371

 

GROUP II:

THEORY

 

 

 

6.840 = or 6.875

 

6.852

 

6.854 = or 6.856

 

GROUP III:=A0 ARTIFICIAL INTELLIGENCE

 

 

6.345 = or 6.866

 

6.825 = or 6.863 or 6.867

 

6.839*

 

*6.839 may be chosen as a second subject in Artificial Intelligence but not as = the only subject in Group III.

 

=A0Each student, with the aid of his = or her graduate counselor, should construct a plan for satisfying the TQE = requirement. This plan should be submitted to the EECS Graduate Office (38-444), on = form 3805 (at the end of the TQE Memo, 3805).=A0 This should be done by registration day of the second = semester.=A0 Each student should plan to = complete TQE courses during their first year, or, with approval of graduate = counselor, no later than the end of the third semester.

TQE oral exams should be taken after all four courses have been completed, = usually by the end of the third semester.=A0=A0

 

=A02.2 The RQE in Area II

 

The RQE is normally taken on or near completion of a Master's research = project or comparable research experience--- preferably at the end of the third = graduate term, and in not later than the end of the fourth graduate = term.

 

The Area II Chair appoints a two person RQE Committee.=A0 The student will provide the committee, two weeks prior = to the exam, a conference-style (less than 20 double-spaced pages) paper based on = original research by the student (usually the SM or MEng thesis).=A0 The RQE Committee conducts an = oral examination in which the student is asked to present his/her research = and to defend it in discussion.=A0 See = Memo 3806 for more details.

 

3. Graduate = Subjects

 

The EECS Department offers a variety of graduate subjects in computer = science and related disciplines.=A0 The = graduate subjects in computer science offered by the EECS Department are = organized into three (overlapping) concentration areas:

 

 

 

 

Systems

 

6.263=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0 = Data communications Networks

6.371=A0 TQE =A0=A0=A0=A0 =A0Introduction to VLSI Systems

6.821=A0 TQE =A0=A0=A0=A0 =A0Programming Languages

6.823=A0 TQE=A0=A0=A0=A0=A0 Computer System = Architecture

6.824=A0 TQE=A0=A0=A0=A0=A0 Distributed Computer = Systems Engineering

6.826=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0 = Principles of Computer Systems

6.827=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0 = Multithreaded Parallelism: Language and Compilers

6.829=A0 TQE=A0=A0=A0=A0=A0 Computer Networks =

6.837=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0 = Computer Graphics

6.846=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0 = Parallel Processing: Systems Architecture and Applications

6.857=A0=A0 =A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0 Network and Computer Security

=A0

Theory

 

6.336=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0 = Introduction to Numerical Algorithms

6.337=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0 = Numerical Methods of Applied Mathematics

6.338=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0 = Parallel Scientific Computing

6.840J TQE=A0=A0=A0=A0 Theory of Computation (grad.version of 6.045)

6.841J=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0 = Advanced Complexity Theory

6.844=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0 = Computability Theory of and with Scheme

6.852J TQE=A0=A0=A0=A0 Distributed Algorithms

6.854J TQE=A0=A0=A0=A0 Advanced Algorithms

6.855J=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0 = Network Optimization

6.856J TQE=A0=A0=A0=A0 Randomized Algorithms

6.859=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0 = Combinatorial Optimization

6.874=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0 = Computational Functional Genomics

6.875J TQE=A0=A0=A0=A0 Cryptography and Cryptanalysis

6.876J=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0 = Advanced Topics in Cryptography

=A0

Artificial = Intelligence

 

6.345 TQE=A0=A0=A0=A0=A0=A0 Automatic Speech Recognition

6.825 TQE=A0=A0=A0=A0=A0=A0 Techniques in Artificial Intelligence

6.833=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0 = Human Intelligence Enterprise

6.834=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0 = Intelligent Embedded Systems

6.836=A0=A0 =A0 =A0=A0=A0=A0=A0=A0=A0=A0=A0 =A0Embodied Intelligence

6.838=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0 = Advanced Topics in Computer Graphics

6.839 TQE=A0 =A0=A0=A0=A0 =A0Advanced Computer = Graphics

6.863J TQE =A0=A0=A0 =A0Natural Language and the Computer Representation of Knowledge

6.866=A0 TQE=A0=A0=A0=A0=A0 Machine Vision = (graduate version of 6.801)

6.867 TQE=A0=A0=A0=A0=A0=A0 Machine Learning and Neural Networks

6.868J=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0 = The Society of Mind

6.871=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0 = Knowledge-Based Applications Systems

6.872J=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0 = Medical Computing

6.873=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0 = Medical Decision Support

 

Specialized seminar subjects, often covering advanced research topics, are offered = on an irregular basis under the course numbers 6.891--9.=A0 Detailed information is available from graduate = counselors on registration day and/or EECS.

 

Numerous additional graduate subjects of interest to Area II students are offered = in other departments of MIT such as Architecture (Course 4), Brain and = Cognitive Sciences (Course 9), Linguistics and Philosophy (Course 24), Management = (Course 15), and Mathematics (Course 18).=A0 = Courses in computer Science taught in the Division of Applied Science at Harvard University are also available through = cross-registration.

 

4. Research in = Computer Science

=A0

Perhaps the most important facet of graduate education in Area II is involvement = in original research.

 

The primary laboratory concerned with computer science research is the = Computer Science and Artificial Intelligence Laboratory (CSAIL).=A0 The Laboratory for Computer = Science and the Artificial Intelligence Laboratory merged on July 1, 2003 to form CSAIL. = Over 750 personnel, including approximately 85 faculty and research = supervising staff and over 300 graduate students, are affiliated with CSAIL.=A0 In addition, there are several = research groups in the Laboratory for Information and Decision Systems, the = Research Laboratory of Electronics, and the Media Laboratory, which make = extensive and sophisticated use of computers and digital technology in their = work.

 

To facilitate involvement in research, entering students are urged to = associate as soon as possible with a research group within a laboratory.=A0 This association is readily = changed if a student's interests change.

 

Summaries of computer science research in Area II can be found in the CSAIL = website http://csail.mit.edu.=A0

=A0

5. Computer = Science Faculty and Research Staff

=A0

In the list below, Roman numerals indicate area affiliations of EECS = faculty.=A0 Affiliations of other faculty and = staff are abbreviated as follows: Department of Mathematics (Math), Department of = Brain and Cognitive Sciences (B&CS), Department of Architecture (Arch), Mechanical Engineering (ME),=A0 = Computer Science and Artificial Intelligence Laboratory = (CSAIL).

=A0

Abelson, = H. (II) = Artificial intelligence, scientific computation, educational computing, societal = and legal frameworks for information technology.

 

Agarwal, = A. (II, III) = Computer architecture and software systems, design of scalable multiprocessor = systems, VLSI processors, compilation and runtime technologies for parallel = processing.

 

Amarasinghe, = S. (II) Program = analysis and optimization, computer architecture.=A0=A0

 

Arvind = (II) = Architecture synthesis and verification, term rewriting systems and Lambda = calculus.=A0 Parallel architectures and = programming languages.

 

Asanovic, = K. (II)=A0 Computer architecture, VLSI = design, energy-efficient computing, parallel computing and embedded = systems.

 

Balakrishnan, = H. (II)=A0 Computer networks, mobile and = sensor computing systems, distributed systems.

 

Barzilay, = R. (II) Natural = Language Processing.

 

Berger, = B. (CSAIL/Math) Algorithms, Computational Biology, Randomness, Parallel = Computation.

 

Berwick, R. = C. (II, = B&CS) Natural language processing: computer models of language acquisition and = parsing. Computational biology and evolutionary theory.=A0 Artificial Intelligence: formal models of learning, including = inductive inference and computational complexity analysis of language.=A0 Cognitive science:=A0 word learning, semantics of natural languages, = speech.=A0

=A0

Braida, = L.=A0 (VII, II, I) Development of aids = for the deaf based on signal processing and automatic speech recognition.=A0 Computational models of hearing = impairment and speech intelligibility.

 

Brooks, R. = A. (II, III) = Humanoid robotics.=A0 Artificial = life.

 

Chan, = V. (I, II, IV) = Optical, wireless and space communications and networks.=A0 Architecture, technology, system designs, and testbed implementations.=A0 New = technology, architectures and applications.

 

Chandrakasan, = A. (III, II, V) = Energy efficient implementation of digital integrated circuits for systems such = as distributed wireless microsensors and portable multimedia devices, the = development of protocols and algorithms for wireless communication, and design methodologies for emerging technologies.=A0

 

Clark, D. = D. (CSAIL) = Computer networks:=A0 Internet = engineering; hardware and protocols for high speed large scale network = communications.=A0 Real-time services over = networks.=A0 Network-host interfacing.=A0 Policy and economic issues; = pricing.

 

Collins, = M. (II ) Natural = Language Processing =96 emphasis on statistical or machine learning = approaches.

 

Darrell, = T. (II) Computer = vision, machine learning, and computer graphics, especially in their application = to problems of human-computer interface.=A0=A0

 

Davis, = R. (II)=A0 Artificial intelligence, = knowledge based systems, natural interaction, sketch understanding; intellectual = property issues in software.

 

Demaine, = E. (II) = Algorithms and data structures.=A0 Discrete = and computational geometry.=A0 = Combinatorial games.

 

Dennis, = J. (CSAIL) = Computer system design to support functional languages and advanced environments for = modular programming.=A0 Study of = architecture, performance and reliability issues.=A0 (Emeritus)

 

Devadas, = S. (II, III) = Computer architecture. Computer security.=A0 Electronic Design Automation.

 

Doyle, = J. (CSAIL) = Artificial intelligence and rational psychology.=A0 Theories and architectures for reasoning, knowledge = representation, and decision making.=A0 Relations = to philosophy, economics, and physics.=A0 Applications to medicine.

 

Durand, = F. (II) Image = generation and creation; realistic rendering, real-time graphics, = perceptually-based algorithms, non-photorealistic rendering, image-based rendering and = editing.

 

Edelman, = A. (CSAIL/Math) Scientific Computing, High Performance Architectures, Numerical = Analysis, Numerical Linear Algebra, Random Matrices.

 

Ernst, = M. (II) Software engineering, programmer productivity tools, reverse engineering, program understanding, programming environments, compilation, program analysis, optimization, programming language design, formal methods, dynamic = analysis, machine learning.

 

Freeman, = W. (II) Machine = learning applied to computer vision, computer graphics, and image = processing.=A0 Bayesian models of visual = perception; example-based image synthesis; belief propagation.

 

Gallager, R. = G. (I, II) = Wireless communication, information theory, all optical networks, data = networks.=A0 (Emeritus)

 

Goemans, = M. (Math, CSAIL) Combinatorial optimization: theory, applications, design and analysis of algorithms, polyhedral combinatorics.

 

Garland, S. = J. (CSAIL) = Practical applications of formal methods to software design and development.=A0 Specifying and reasoning about = distributed systems and network protocols.=A0 Automated deduction.=A0 Software-based signal processing.

 

Gifford, D. = K.(II) = Biological computing.=A0 Computer = systems.

=A0

Glass, = J. (CSAIL)=A0 Automatic speech recognition, = synthesis, and understanding for multi-modal, conversational = interaction

 

Goldwasser, = S. (II)=A0 Cryptography, pseudo randomness, = property testing,=A0 computational = number

theory, multi-party computations.

 

Golland, = P. (II) = Developing novel techniques for image analysis and understanding.

=A0

Grimson, W. = E. (II) Computer = vision, image databases, medical image processing, image guided surgery, = activity recognition, scene reconstruction.

 

Guttag, J. = V. (II) Medical = software, wireless networking.

 

Hanson, = C. (CSAIL) VLSI mixed-signal design.=A0 Radio communications.=A0 Signal = processing.

 

Horn, B. K. = P. (II) Machine = vision, diaphanography.=A0 = Representation of objects and space.=A0 = Photogrammetry, analog networks, computing images.=A0=A0

 

Indyk, = P. (II) = Computational geometry, especially in high-dimensional spaces; databases and = information retrieval; learning theory; design and analysis of = algorithms.

 

Jaakkola, = T. (II) = Statistical inference and machine learning. Applications to computational biology = and information retrieval.=A0 = Artificial intelligence.

 

Jackson, = D. (II) Software = design and specification; design methods, tools and analysis; dependability; safety-critical systems; reverse engineering; static analysis, model = checking, programming languages.

 

Kaashoek, = F. (II) Computer systems:=A0 operating systems, = networking, programming languages, compilers, and computer architecture for = distributed systems, mobile systems and parallel systems.

 

Kaelbling, = L. (II) = Integrating learning modules into systems programmed by humans, algorithms for = planning and learning in partially observable environments, learning complex models = from perceptual information.

 

Karger, = D. (II) = Information retrieval and digital libraries; analysis of algorithms, especially for = graphs and optimization problems; applications of randomization; parallel algorithms.=A0 =

 

Katabi, = D (II) Computer = networks, data communication.

 

Knight, T. = F. (CSAIL) = Computer architectures and programming languages for artificial intelligence applications, image and auditory perception.=A0 Physics of computation.=A0 = High speed digital design.

 

Lampson, B. = W. (II) Computer science.=A0=A0 Hardware design = and machine architecture through distributed systems and programming languages to = user interfaces and office automation.=A0 =

 

Larson, R. = C. (I, II) = Applying advanced technologies to education in both the ``brick-and-mortar'' and = virtual campus. Probability methods applied to services = industries.

 

Leighton, F. T. = L. = (CSAIL/Math)=A0 Internet Algorithms.=A0 Parallel algorithms and = architectures. Probabilistic analysis of algorithms.=A0 Combinatorial methods.=A0 Fault-Tolerance in networks.=A0=A0

 

Leiserson, C. = E. (II) Theory = of computing machinery, parallel computation, graph theory, algorithms, = computer architecture, supercomputing, multithreading.

 

Liskov, B. = H.(II) Programming = methodology, programming languages, distributed systems,

object-oriented databases.

 

Long, = W. (CSAIL ) = Application of artificial intelligence techniques to medical = decision

making, particularly in cardiology.=A0 = Effective use of physiologic modeling, probabilistic networks, and machine = learning.=A0 Web based tools to help patients = manage their health in the home.

 

Lozano-Perez, = T. (II)=A0 Artificial intelligence.=A0 Computational chemistry and = biology.=A0 Robotics and computer = vision.

 

Lynch, N. = A. (II) = Theoretical aspects of distributed computing.=A0 = Distributed algorithm and system design, impossibility results.=A0 Semantics, formal modeling, verification, and = performance analysis.

Languages and tools for abstract distributed programming.=A0 Hybrid (continuous/discrete) = systems.

 

Madden, = S. (II) = Systems-oriented database research; focus on adaptive database systems and data = processing in the context of sensor networks.

 

Magnanti, = T. (I, II) = Network design.=A0 Network = equilibrium.=A0 Large-scale optimization.=A0 Optimization in = telecommunications, manufacturing, logistics, and transportation.

 

Margolus, N. = H. (CSAIL) = Highly parallel architectures, spatial-lattice computers and computations, = physical modeling, physics of computation, reversible computation, quantum = computation.

 

Megretski, = A. (I, II) = Theory and algorithms of analysis and design of hybrid systems, nonlinear and = robust control, non-convex and convex optimization, formalization of knowledge = in education, functional analysis and operator theory.=A0=A0

 

Meyer, A. = R. (II) Software education environments.=A0 = Semantics of programming languages, logic+ of programs, concurrent programs, Lambda calculus.

 

Micali, = S. (II) = Cryptography, secure protocols, and computational complexity = theory.

 

Miller, = R. (II) = Human-computer interfaces, intelligent interfaces, programming by demonstration, = end-user programming languages, usability, software = engineering.

 

Minsky, M. = L. (II) = Artificial intelligence. Robotics and machine vision.=A0 Representation of knowledge and structure of personality. Common = sense reasoning, theories of emotion and consciousness.=A0 (Emeritus)

 

Mitter, S. = K. (I, II) = Theory of stochastic dynamical systems, nonlinear filtering, stochastic and = adaptive control.=A0 Mathematical = physics and its relationship to systems theory.=A0 = Image analysis and computer vision.=A0 Structure, function and organization of complex = systems.

 

Morris, R. = T. (II) The = design of an easy to control data networking infrastructure designed to bring about a = new level of flexibility to network configuration.=A0 The Resilient Overlay Networks Project.=A0 Grid routing protocols.=A0=A0 =

 

Moses, = J. (II) = Organization of large complex systems, software production, knowledge based systems, and symbolic manipulation.

 

Penfield, Jr., = P. L. (III, II, V) Information and entropy.=A0 =

 

Poggio, = T. (B&CS, = CSAIL ) Statistical Learning: theory, algorithms and applications. Computer and =

Human Vision.

 

Popovic, = J. (II) Geometric modeling, the design of shapes; computer animation, the design of = motion.=A0 Computer graphics, human-computer = interaction, biomechanics, robotics, and design.

 

Rinard, = M. (II)=A0 Program analysis, transformation, instrumentation, and compilation techniques, with an emphasis on = applying these techniques to object-oriented, real-time, distributed, and parallel = systems.

 

Rivest, R. = L. (II) = Cryptography. Computer/Network Security. Algorithms.

 

Rus, = D. (II) = Robotics, Mobile Computing, Sensor Networks, Information Access.

 

Saltzer, J. = H.(II) Computer = systems and computer networks. (Emeritus.)

 

Sarpeshkar, = R. (III, I, VII, = II ) Analog VLSI for adaptive sensory and neural systems including audition, vision, = and micromechanical systems.=A0 = Hybrid (analog-digital) spike-based VLSI computation:=A0 low-power analog-to-digital conversion, digital arithmetic and = sequence recognition.=A0 Analog VLSI for = bionic applications, especially speech processors for the = deaf.

 

Seneff, S. = (CSAIL) Spoken Conversational Systems, spoken language understanding and generation, genomics.

 

Shrobe, = H.(CSAIL) = Artificial intelligence; The Intelligent Room; Information Survivability; = Self-Adaptive Software.

 

Sipser, = M. (CSAIL/Math) Computational complexity theory, probabilistic methods, analysis of = algorithms, mathematical logic.

 

Sollins, K. = R. (CSAIL) = Pervasive systems and networks, information systems and infrastructure, naming, = and security

 

Spielman, = D. (CSAIL/Math) = Analysis and Design of Algorithms, Error-Correcting Codes, Complexity = Theory.

 

Sudan, = M. (II) = Complexity of finding 'approximate' solutions to combinatorial optimization problems; interplay of algebra with computer science and coding = theory.

 

Sussman, G. = J. (II) = Artificial intelligence: basic research on learning, problem solving and = programming.=A0 Computational performance models = for intelligent behavior, especially modelling the behavior of engineers. = =A0Numerical models of physical = systems.

 

Szolovits, = P. (II) = Application of artificial intelligence techniques to medical decision making.=A0 Effective representation of = knowledge. Personal health information systems, medical = confidentiality.

 

Teller, = S. (II) Computer graphics; photorealistic image synthesis; real-time visual simulation; reconstruction of geometric models from instrumented imagery; = interaction with complex geometric datasets; applied computational = geometry.

 

Terman, = C. (CSAIL) = Computer and DSP architectures; VLSI circuits; design methodologies and CAD tools; = circuit simulation; computer languages.

 

Tidor, = B. (II, VII) = Computational Biology and Chemistry, Protein and Systems Modeling, Molecular = Biophysics, Rational Drug Design, Electrostatic Optimization.

 

Troxel, D. = E. (III, II) = Applications of digital systems.=A0=A0 =

 

Tsitsiklis, J. = N. (I, II) = Analysis, optimization and algorithms for deterministic and stochastic = systems.=A0 Resource allocation in dynamic environments.=A0 Communication = networks.=A0

 

Vempala, = S. (CSAIL/Math) Algorithms. Randomness, Geometry, Combinatorics. = Information

retrieval.=A0=A0

 

Ward, S. = A. (II) Computer architecture and operating systems.

 

White, J. = K. (III, II, I) Simulation and optimization techniques for design problems in the fields = of integrated circuit interconnect and packaging, micromachined devices = (MEMS), and biodevices (BIOMEMS).=A0 =

 

Winston, P. = H. (II) = Artificial intelligence.=A0 Role of vision = and language in computational explanation of human = intelligence.

 

Wroclawski, = J. (CSAIL) = Distributed systems. High performance network protocols. Upper layer network architecture.=A0 = Graphics.

 

Zue, V. = W. (II, VII) = Human-human and human-machine communication using spoken and written languages.=A0 Audio/visual cue = integration.=A0 Detection and rendering of = paralinguistic information.=A0 = Acoustic-phonetic=A0 analysis of=A0 speech and strategies for lexical access..

 

=A0

 

 

 

 

 

 

 

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