Faculty

Professor of Electrical Engineering and Computer Science

Machine learning applies to any situation where there is data that we are trying to make sense of, and a target function that we cannot mathematically pin down. The spectrum of applications is huge, going from financial forecasting to medical diagnosis to industrial inspection to recommendation systems, to name a few. The field encompasses neural networks, statistical inference, and data mining.

Professor of Computer Science

Professor Barr's research involves (1) mathematical simulation methods for computer graphics (2) developing new types of mathematical and computational methods for the study of biophysical behaviors and structures and (3) technological leveraging for medical health care and new medical devices.

George W. Housner Professor of Engineering and Applied Science

Professor Beck focuses on the development of theory and algorithms for stochastic system modeling, uncertainty propagation and Bayesian updating of dynamic systems, treating both modeling and excitation uncertainty. The primary computational tools are advanced stochastic simulation algorithms based on Markov chain Monte Carlo concepts. Some applications of current interest are the stochastic prediction of performance of structural systems under earthquakes, fast automated decision making for mitigation actions based on earthquake early warning systems, earthquake source inversions from seismic sensor networks, damage detection and assessment from structural sensor monitoring networks, and a stochastic mechanics approach to quantum mechanics.

Professor of Applied and Computational Mathematics

Our efforts concern development of accurate, high-performance numerical PDE solvers applicable to realistic scientific and engineering configurations. Major theoretical and computational difficulties arise in associated areas of PDE theory, numerical analysis and computational science as a result of manifold complexities, including intricate geometries, solution singularities, resonances, nonlinearities, high-frequencies, dispersion, etc. Fourier Continuation (FC) and integral-equation techniques recently developed in our group have enabled accurate solution of previously intractable PDE problems of fundamental importance in science and engineering.

Professor of Mechanical Engineering and Bioengineering

Professor Burdick focuses on robotics, kinematics, mechanical systems and control. Active research areas include: robotic locomotion, sensor-based motion planning algorithms, multi-fingered robotic manipulation, applied nonlinear control theory, neural prosthetics, and medical applications of robotics.

Simon Ramo Professor and Professor of Computer Science; Deputy Chair for Education

Professor Chandy builds and analyzes systems that sense and respond to changes. He is currently working on systems that sense and respond to: (a) seismic events, (b) threat events such as the introduction of nuclear radiation material, (c) medical events such a fetal distress, and (d) events in the power grid. The systems use sensor networks, cloud computing and event-driven architecture. The theory is based on optimization, control, machine learning and game theory.

Professor of Computing and Mathematical Sciences; Director of Computing and Mathematical Sciences, and Information Science and Technology

Professor Desbrun focuses on discrete differential modeling—the development of differential, yet readily discretizable foundations for computational modeling—and a wide spectrum of applications, ranging from discrete geometry processing to solid and fluid mechanics as well as field theory.

John G Braun Professor of Control and Dynamical Systems, Electrical Engineering, and Bioengineering

Professor Doyle focuses on integrating modeling, ID, and analysis and design of uncertain nonlinear systems.

Assistant Professor of Electrical Engineering and Computer Science

Tracey Ho's research investigates fundamental limits on and strategies for efficient and robust network communication, using techniques from coding and information theory.

Charles Lee Powell Professor of Applied and Computational Mathematics

Professor Hou focuses on modeling, computation, and mathematical analysis of vortex dynamics, interfacial flows, and multiscale problems. His recent research interests include fundamental problems such as the global regularity or possible finite time blow-up of the 3D Navier-Stokes equations, multiscale modeling of 3D incompressible flows, data-driven stochastic multiscale methods, and adaptive data analysis for nonlinear and nonstationary data.

Professor of Theoretical Physics, Computer Science, and Mathematics

Professor Kitaev works in the field of quantum computation and related areas of theoretical physics. His main contribution was the concept of topological quantum computation, a scheme where quantum information is protected from errors due to special properties of the underlying physical system, which are generally related to topology. He currently focuses on topological classification of quantum phases (a nontrivial example being the 2-dimensional electron liquid in the quantum Hall regime).

Assistant Professor of Computer Science

Professor Krause's research is in adaptive systems that actively acquire information, reason and make decisions in large, distributed and uncertain domains, such as sensor networks and the Web. The theoretical aspects include statistical (Bayesian) learning and modeling, decision theory and optimization. His group devises new algorithms, builds models, analyzes large and complex data sets and develops systems that can automatically acquire and reason about highly uncertain information. 

Allen and Lenabelle Davis Professor of Economics and Social Sciences

Assistant Professor of Computer Science and Economics

Professor Ligett's research focuses on mathematical and computational approaches to fundamental problems in algorithmic game theory and in data privacy, with a particular emphasis on techniques from computational learning theory.

Professor of Computer Science and Electrical Engineering

Control and optimization of communication and cyber-physical networks such as the Internet and power networks. Current research focuses on fundamental issues in network architecture; green IT especially energy efficiency of next generation datacenters; and all aspects of smart grids, including analysis, design and deployment of information and communication technologies in power networks, integration of renewable and distributed generation, demand response, electricity market design and games. Emphasis is on the interplay between theory, algorithms, prototyping, and experimental studies to maximize potential impact.

Professor of Computer Science

Professor Martin focuses on asynchronous VLSI and parallel architecture.

Fletcher Jones Professor of Aeronautics and Applied and Computational Mathematics; Associate Director, Graduate Aerospace Laboratories

Professor Meiron's research focuses on computation and modelling of basic fluid mechanical phenomena. Particular interests include shock driven flow instabilities, turbulence, simulation approaches for high strain rate solid mechanics. He is also interested on development of adaptive numeriocal methods for such flows that are suitable for high performance computation.

Thomas E. and Doris Everhart Professor of Control and Dynamical Systems and Bioengineering

Research in Richard Murray's group is in the application of feedback and control to networked systems, with applications in biology and autonomy. Current projects include novel control system architectures, biomolecular feedback systems and networked control systems.

Professor of Applied and Computational Mathematics and Control and Dynamical Systems

Professor Owhadi focuses on the modeling and analysis of systems characterized by multiple scales, geometric structures, noise and uncertainties.
At the center of his work are fundamental problems such as non-separated scales, anomalous diffusion, the geometric integration of multi-scale stochastic mechanical systems and the optimal quantification of uncertainties in presence of limited information.

Allen E. Puckett Professor of Electrical Engineering

Professor Perona's research focusses on vision: how do we see and how can we build machines that see.

Professor Perona has been mostly active in the area of visual recognition, more specifically visual categorization. He is studying how machines can learn to recognize frogs, cars, faces and trees with minimal human supervision, and how one could make large image collections and even the web searchable by image content.

In collaboration with Professors Anderson and Dickinson, professor Perona is building vision systems and statistical techniques for measuring actions and activities in fruit flies and mice. This enables geneticists and neuroethologists to investigate the relationship between genes, brains and behavior.

Professor Perona is also interested in studying how humans perform visual tasks, such as searching and recognizing image content. One of his recent projects studies how to harness the visual ability of thousands of people on the web for classifying and searching image content.

Professor of Applied and Computational Mathematics and Bioengineering; Executive Officer for Bioengineering

The Pierce Lab is focused on engineering small conditional RNAs that interact and change conformation to execute molecular logic in vitro, in situ, and in vivo. To read out and regulate the state of biological systems, we seek to engineer small conditional RNAs that function as programmable molecular instruments within intact biological specimens. To eliminate side effects associated with conventional chemotherapies, we seek to engineer small conditional RNAs that function as conditional chemotherapies, selectively activating in diseased cells, while leaving normal cells untouched. To enable the systematic design of small conditional RNAs that execute diverse dynamic functions, we are working to develop mathematically rigorous, physically sound, computationally efficient algorithms for programming molecular function.

Richard P. Feynman Professor of Theoretical Physics

Professor Preskill works on quantum computation and quantum information science. He is especially interested in methods for protecting quantum states from damage, and in applications of quantum information concepts to problems in physical science.

Professor of Computer Science and Applied and Computational Mathematics

Prof. Schröder is interested in the design of efficient and reliable algorithms for problems in computer graphics. These range from geometric modeling (effective methods to model the shape of objects) to animation (simulation of physical phenomena such as the deformation of cloth). His emphasis is on an area known as "Discrete Differential Geometry." Its goals are to rebuild the foundations of classical differential geometry in a discrete setting which makes it immediately useful for computation.

Professor of Computer Science

Professor Schulman's research is in several overlapping areas: algorithms and communication protocols; combinatorics and probability; coding and information theory; quantum computation.

Assistant Professor of Applied and Computational Mathematics

Professor Tropp's recent research focuses on the role of probability and optimization in numerical analysis and scientific computing. In particular, he studies algorithms for signal processing and modern data analysis that exploit randomness. The relevant mathematics include applied harmonic analysis, probability theory, discrete and convex geometry, variational analysis, and multilinear algebra. Ideas from theory of algorithms also play a central role.

Professor of Computer Science

Professor Umans is interested in theoretical computer science, and especially computational complexity. He enjoys problems with an algebraic flavor, and this often leads to research questions in derandomization and explicit combinatorial constructions, algebraic algorithms, coding theory, and hardness of approximation.

Assistant Professor of Computer Science

Wierman's research interests are best summarized as: "Better design through modeling and measurement." His work applies and often extends techniques in stochastic modeling, queueing theory, scheduling theory, and game theory in order to provide insight into the impact of design decisions in systems such as data centers, wireless networks, social networks, electricity grids, and beyond.

Professor of Computer Science, Computation and Neural Systems, and Bioengineering

Professor Winfree's research involves theoretical and experimental aspects of molecular programming. Models of computation are developed that incorporate essential features of molecular folding, molecular self-assembly, biochemical circuits, and molecular robotics. These models are studied to determine their expressiveness for programming behaviors such as memory, behavior, and morphogenesis.  Methods for compiling abstract molecular programs into actual molecules are developed and tested in the laboratory.

Charles Lee Powell Professor of Applied Mathematics, Emeritus

Gordon and Betty Moore Professor of Engineering and Applied Science, Emeritus

Professor Mead's interests include the creation of silicon models of specific areas of the nervous system, and the physics of computation.

Professor of Applied Philosophy and Computer Science, Emeritus