Professor Bertsekas has done research in a variety of fields that involve principally optimization theory, and its applications in communication and control, such as: linear and nonlinear programming, network optimization, dynamic and neuro-dynamic programming, estimation and control of stochastic systems, neural networks, parallel and distributed computation, data communication networks.  He has written several books and numerous research papers.

• http://www.mit.edu/people/dimitrib/home.html

 Research Interests include:  Optimal and Robust control synthesis with logic and discrete constraints, Model Reduction of Stochastic Hybrid Systems, Distributed control of Network Systems, Learning in Games and Application to Social Modeling, Learning compex hypotheses and application to system identification, and Neuro-biology with focus on cerebellar control and understanding cortical oscillations.

• http://web.mit.edu/dahleh/www/index.htm

DiCarlo joined the McGovern Institute in 2002, and is an associate professor in the Department of Brain and Cognitive Sciences. He received his Ph.D. and M.D. from Johns Hopkins University and did postdoctoral work at Baylor College of Medicine. In 1998, he received the Martin and Carol Macht Young Investigator Research Prize from Johns Hopkins University. In 2002, he received an Alfred P. Sloan Research fellowship and a Pew Scholar Award. He received MIT's Surdna Research Foundation Award and its School of Science Prize for Excellence in Undergraduate Teaching in 2005, and he won a Neuroscience Scholar Award from the McKnight Foundation in 2006.

John Fisher is a principal research scientist at MIT.  Lately he has been working on signal level approaches to multi-modal data fusion, distributed inference under resource constraints, resource management in sensor networks, and analysis of seismic and radar images.

• http://people.csail.mit.edu/fisher/

Research interests include: stochastic processes and queueing theory, applications to business processes, probabilistic combinatorics, algorithms and combinatorial optimization, scheduling, and statistical learning theory.

• http://www.mit.edu/~gamarnik/home.html

As a faculty member of the Control Systems Group in the Laboratory for Information and Decision Systems (LIDS) in the MIT Electrical Engineering and Computer Science (EECS) department, my research interests cover: Nonlinear dynamical system analysis, Design and validation of hybrid control algorithms, Optimization (LP,LMI,convex,non-convex etc.), Applications: flight control, control of production, control of animated objects, relay systems.  Currently I am supervising several graduate students on a project to design and create a MATLAB toolbox for optimization-based system identification, model reduction, and robust inference.

• http://web.mit.edu/ameg/www/

Professor Mitter's research has spanned the broad areas of Systems, Communication and Control. Although his primary contributions have been on the theoretical foundations of the field, he has also contributed to significant engineering applications, notably in the control of interconnected power systems and pattern recognition.
His current research interests are theory of stochastic and adaptive control; mathematical physics and its relationship to system theory; image analysis and computer vision; and structure, function and organization of complex systems.

• http://web.mit.edu/~mitter/www/

Research Interests: Nonlinear optimization and convex analysis,
Game theory, Network economics; pricing and resource allocation games,
Distributed optimization methods, Network optimization and control; wireless and wireline network

• http://web.mit.edu/asuman/www/

Dr. Parrilo is interested in game theory, computational mathematics, operator theory, and control systems

• http://www.mit.edu/~parrilo/

      name: Polydorides, Nicholas
     email: nickpld@MIT.EDU
     phone: (617) 452-3872
   address: 32D-566
department: MIT Energy Initiative
     title: Postdoctoral Associate
       url: http://www.mit.edu/~nickpld

Devavrat Shah is currently a Jamieson career development assistant professor with the department of electrical engineering and computer science, MIT. He is a member of the Laboratory of Information and Decision Systems (LIDS). His research focus is on theory of large complex networks which includes network algorithms, stochastic networks, and network information theory and large scale statistical inference.

• http://www.mit.edu/~devavrat/

Russ Tedrake is an Associate Professor in the Department of Electrical Engineering and Computer Science at MIT, and a member of the Computer Science and Artificial Intelligence Lab. He received his B.S.E. in Computer Engineering from the University of Michigan, Ann Arbor, in 1999, and his Ph.D. in Electrical Engineering and Computer Science from MIT in 2004, working with Sebastian Seung. After graduation, he spent a year with the MIT Brain and Cognitive Sciences Department as a Postdoctoral Associate. During his education, he has spent time at Microsoft, Microsoft Research, and the Santa Fe Institute.

Professor Tedrake's research group is interested in underactuated motor control systems in animals and machines that are capable of executing dynamically dexterous tasks and interacting with uncertain environments. They believe that the design of these control systems is intimately related to the mechanical designs of their machines, and that tools from machine learning and optimal control can be used to exploit this coupling when classical control techniques fail. Current projects include robust and efficient bipedal locomotion on flat terrain, multi-legged locomotion over extreme terrain, flapping-winged flight, and feedback control for fluid dynamics.

Research areas:
Communication networks (Resource Allocation, Games, Queueing), Neuro-Dynamic Programming (Large scale dynamic programming and reinforcement learning), Analysis and control of stochastic systems
Computational complexity in systems and control, Dijkstra-like methods for the eikonal equation ("Fast marching"), Flocking and consensus, Parallel and distributed computation, Data fusion (Communication complexity and decentralized detection), Optimization, control, and system identification, and Estimation and learning

• http://web.mit.edu/jnt/www/home.html

Dr. Willsky is the MIT ISAMI Director.  He is a Professor in the Dept. of Electrical Engineering and Computer Science at MIT. Dr. Willsky's present research interests are in problems involving multidimensional and multiresolution estimation and imaging, and particularly in the development and application of advanced methods of estimation and statistical signal and image processing. Methods he has developed have been successfully applied in a wide variety of applications including failure detection in high-performance aircraft, advanced surveillance and tracking systems, electrocardiogram analysis, computerized tomography, and remote sensing.

• http://ssg.mit.edu/~willsky/

David Goldberg is a Ph.D student at MIT in Operations Research.  His research interests are probabilistic combinatorics, queueing, scheduling and networks.

I am a Ph.D. Student in MIT Mathematics and LIDS, supervised by Prof. Devavrat Shah. My research interests are theoretical aspects of algorithms on the computer science, stochastic networks and economics. Especially, I love to see beautiful mathematics meets a simple algorithm. Currently, I am working on the field of Scheduling algorithms, Belief Propagation and Dynamics of games.

Degree Program Ph.D

Mengdi's advisor at MIT is Professor Dimitri Bertsekas.

Research Directorate(s): AI    Research: Robotics

• http://www.csail.mit.edu/people/1305

I am currently a Ph.D. student in Electrical Engineering at MIT, working in the Computational Prototyping Group under Professor Luca Daniel.

My main reserach interests are in modeling and simulation for the purpose of automatic design and optimiziation of systems such as analog circuits and MEMS devices. This includes both theoretical issues concerning modeling of nonlinear systems, such as guaranteed preservation of stability, and practical issues concerning fast simulation.

Currently, my research is towards the automatic system-level design and optimization of RF receiver chains. Specifically, my work focuses on the automatic extraction of parameterized compact models for both linear and nonlinear receiver components such as amplifiers, mixers, and parasitic interconnects. To this end, I have developed and improved several modeling techniques based on nonlinear model reduction and system identification, and have worked on preserving system properties such as stability and passivity in the resulting macromodels.

Mitra Osqui is a graduate student and research assistant at MIT working on optimization-based design of reduced complexity nonlinear signal processing systems.