Joining Caltech this year:
Aaron Ames
Aaron Ames

Professor Ames’ research interests center on robotics, nonlinear control, hybrid systems and cyber-physical systems, with special emphasis on foundational theory and experimental realization on robotic systems; his lab designs, builds and tests novel bipedal robots and prosthesis with the goal of achieving human-like bipedal robotic walking and translating these capabilities to robotic assistive devices.

Animashree (Anima) Anandkumar
Animashree (Anima) Anandkumar

Professor Anandkumar's research interests are in the areas of large-scale machine learning, non-convex optimization and high-dimensional statistics. In particular, she has been spearheading the development and analysis of tensor algorithms for machine learning. Tensor decomposition methods are embarrassingly parallel and scalable to enormous datasets. They are guaranteed to converge to the global optimum and yield consistent estimates for many probabilistic models such as topic models, community models, and hidden Markov models. More generally, Professor Anandkumar has been investigating efficient techniques to speed up non-convex optimization such as escaping saddle points efficiently.

Lior Pachter
Lior Pachter

Professor Patcher is a computational biologist working in genomics. His career began in comparative genomics, and initially was interested in genome alignment, annotation, and the determination of conserved regions using phylogenetic methods. More recently he's become focused on functional genomics, which includes answering questions about the function and interaction of DNA, RNA and protein products. He's particularly interested in applications of high-throughput sequencing to RNA biology. Genomics requires the development of algorithms, statistical methodology and mathematical foundations, and a major part of his research is therefore on methods.

Faculty

Yaser S. Abu-Mostafa

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.

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Aaron Ames

Bren Professor of Mechanical and Civil Engineering and Control and Dynamical Systems

Professor Ames’ research interests center on robotics, nonlinear control, hybrid systems and cyber-physical systems, with special emphasis on foundational theory and experimental realization on robotic systems; his lab designs, builds and tests novel bipedal robots and prosthesis with the goal of achieving human-like bipedal robotic walking and translating these capabilities to robotic assistive devices.

Research Group
Animashree (Anima) Anandkumar

Bren Professor of Computing and Mathematical Sciences

Professor Anandkumar's research interests are in the areas of large-scale machine learning, non-convex optimization and high-dimensional statistics. In particular, she has been spearheading the development and analysis of tensor algorithms for machine learning. Tensor decomposition methods are embarrassingly parallel and scalable to enormous datasets. They are guaranteed to converge to the global optimum and yield consistent estimates for many probabilistic models such as topic models, community models, and hidden Markov models. More generally, Professor Anandkumar has been investigating efficient techniques to speed up non-convex optimization such as escaping saddle points efficiently.

Alan H. Barr

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.

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Oscar P. Bruno

Professor of Applied and Computational Mathematics

Prof. Bruno's work focuses on development of accurate, high-performance numerical PDE solvers capable of modeling faithfully 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 intricate and/or singular geometries as well as solution singularities, resonances, nonlinearities, high-frequencies, dispersion, etc. Recently developed Fourier Continuation (FC) and integral-equation techniques, which can successfully tackle such challenges, have enabled accurate solution of previously intractable PDE problems of fundamental importance in science and engineering.

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Joel W. Burdick

Richard L. and Dorothy M. Hayman Professor of Mechanical Engineering and Bioengineering; Jet Propulsion Laboratory Research Scientist

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.

Venkat Chandrasekaran

Professor of Computing and Mathematical Sciences and Electrical Engineering

Chandrasekaran’s research interests lie in mathematical optimization and its application to the information sciences.

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Mathieu Desbrun

Carl F Braun Professor of Computing and Mathematical Sciences

Applied geometry (geometry processing and computer graphics); Discrete differential modeling (differential, yet readily-discretizable tools for computational modeling).

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John Doyle

Jean-Lou Chameau Professor of Control and Dynamical Systems, Electrical Engineering, and Bioengineering

Doyle's research is on theoretical foundations for complex tech, bio, med, neuro, and social networks integrating control, communications, computing, and multiscale physics. Layered architectures such as brains integrate high level planning with fast lower level sensing, reflex, and action and facilitate learning, adaptation, augmentation (tools), and teamwork, despite being implemented in energy efficient hardware with sparse, quantized, noisy, delayed, and saturating sensing, communications, computing, and actuation, on time scales from milliseconds to minutes to days.  We are developing a mathematical framework that deals with all of these features and constraints in a coherent and rigorous way with broad applications in science and technology.

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Yizhao T. (Thomas) Hou

Charles Lee Powell Professor of Applied and Computational Mathematics

Professor Hou focuses on multiscale problems arising from geophysical applications and fluid dynamics, the Millennium Problem on the 3D incompressible Navier-Strokes equations, model reduction for stochastic problems with high dimensional input variables, and adaptive data analysis.

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Katrina Ligett

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.

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Steven Low

Professor of Computer Science and Electrical Engineering

Power systems, cyber-physical systems, network architecture, energy-efficient networking.

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Dan Meiron

Fletcher Jones Professor of Aeronautics and Applied and Computational Mathematics

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.

Research Group
Richard M. Murray

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.

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Houman Owhadi

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.

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Lior Pachter

Bren Professor of Computational Biology and Computing and Mathematical Sciences

Professor Patcher is a computational biologist working in genomics. His career began in comparative genomics, and initially was interested in genome alignment, annotation, and the determination of conserved regions using phylogenetic methods. More recently he's become focused on functional genomics, which includes answering questions about the function and interaction of DNA, RNA and protein products. He's particularly interested in applications of high-throughput sequencing to RNA biology. Genomics requires the development of algorithms, statistical methodology and mathematical foundations, and a major part of his research is therefore on methods.

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Niles A. Pierce

Professor of Applied and Computational Mathematics and Bioengineering

Engineering small conditional DNAs and RNAs for signal transduction in vitro, in situ, and in vivo; computational algorithms for the analysis and design of nucleic acid systems; programmable molecular instruments for readout and regulation of cell state.

Research Group
Peter Schroeder

Shaler Arthur Hanisch Professor of Computer Science and Applied and Computational Mathematics

Professor 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.

Leonard J. Schulman

Professor of Computer Science

Algorithms and Communication Protocols; Combinatorics and Probability; Coding and Information Theory; Quantum Computation.

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Andrew Stuart

Bren Professor of Computing and Mathematical Sciences

Professor Stuart's research is focused on the development of mathematical and algorithmic frameworks for the seamless integration of models with data. He works in the Bayesian formulation of inverse problems, and in data assimilation for dynamical systems. Quantification of uncertainty plays a significant role in this work. Current applications of interest include a variety of problems in the geophysical sciences, and in graph-based learning.

Joel A. Tropp

Steele Family Professor of Applied and Computational Mathematics

Joel Tropp's work lies at the interface of applied mathematics, electrical engineering, computer science, and statistics. This research concerns the theoretical and computational aspects of data analysis, sparse modeling, randomized linear algebra, and random matrix theory.

Research Group
Christopher Umans

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.

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Thomas Vidick

Associate Professor of Computing and Mathematical Sciences

Thomas Vidick's research is situated at the interface of theoretical computer science, quantum information and cryptography. He is interested in using complexity theory as a lens to approach fundamental problems in quantum computing. He has investigated the role of entanglement in multi-prover interactive proof systems and obtained the first substantial computational hardness results on the power of entangled provers. He has made important contributions to the field of device-independent cryptography, where the property of entanglement monogamy plays a key role. His work also demonstrates that insights from quantum information theory can be productively transferred to yield novel perspectives on fundamental techniques in theoretical computer science such as semidefinite programming and approximation algorithms.

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Adam Wierman

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

Adam Wierman's research focuses on three seemingly distinct areas: networks, economics, and energy. Though diverse, the areas are each essential to his broader research goal: easing the incorporation of renewable energy into IT and, more generally, into the electricity grid. His work toward this goal is diverse in both area and technique.  It not only draws on tools from algorithms, networking, operations research, economics, and control -- starting from theory and continuing through implementation to industrial transfer.

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Erik Winfree

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 molecular-level tasks including decision-making, memory, behavior, and morphogenesis.  Methods for compiling abstract molecular programs into actual molecules are developed and tested in the laboratory.

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Yisong Yue

Assistant Professor of Computing and Mathematical Sciences

Yisong Yue's research interests lie primarily in the theory and application of statistical machine learning. He is particularly interested in developing novel methods for structured prediction, spatiotemporal reasoning, adaptive learning systems, and learning with humans in the loop. In the past, his research has been applied to information retrieval, content recommendation, text classification, learning from rich user interfaces, analyzing implicit human feedback, data-driven animation, sports analytics, policy learning in robotics, and adaptive routing and allocation problems.

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Affiliated Faculty

Fernando Brandao

Bren Professor of Theoretical Physics

Fernando Brandão's research is focused on quantum information science. He explores the interplay of physics, computer science and mathematics to study the role of quantum mechanics in computation and information transmission. He is also interested in the application of tools and concepts of quantum information to other branches of science, such as quantum many-body theory, complexity theory and thermodynamics/statistical mechanics. In recent years he has been exploring several directions in entanglement theory, from understanding the relation between entanglement and other physical properties (such as correlation length) in quantum many-body systems, to developing a sharper understanding of fundamental properties of entanglement such as its monogamous character (with applications in quantum cryptography, quantum Hamiltonian complexity, and even in convex optimisation).

Soon-Jo Chung

Associate Professor of Aerospace and Bren Scholar; Jet Propulsion Laboratory Research Scientist

Professor Chung's research focuses on distributed spacecraft systems, space autonomous systems, and aerospace robotics, and in particular, on the theory and application of complex nonlinear dynamics, control, estimation, guidance, and navigation of autonomous space and air vehicles.

Research Group
Frederick Eberhardt

Professor of Philosophy

Frederick Eberhardt's research interests lie at the formal end of philosophy of science, the machine learning end of statistics and computer science, and the learning and modeling end of psychology and cognitive science. His work has focused primarily on methods for causal discovery from statistical data, the use of experiments in causal discovery, the integration of causal inferences from different data sets and the philosophical issues at the foundations of causality and probability. He has done some work on computational models in cognitive science and some historical work on the philosophy of Hans Reichenbach, especially his frequentist interpretation of probability.

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Babak Hassibi

Mose and Lillian S. Bohn Professor of Electrical Engineering

Hassibi's research is in communications, information theory, signal processing, and control. He is currently most interested in various information-theoretic and algorithmic aspects of wireless communications, especially wireless networks. Other interests include adaptive signal processing and neural networks; blind channel equalization; statistical signal processing; robust estimation and control, especially connections between robustness and adaptation; and linear algebra, with emphasis on fast algorithms, random matrices and group representation theory.

Research Group
Alexei Kitaev

Ronald and Maxine Linde Professor of Theoretical Physics 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).

Victoria Kostina

Assistant Professor of Electrical Engineering

Victoria Kostina's research spans information theory, coding, and wireless communications. Her current efforts explore one of the most exciting avenues in today's information theory: the nonasymptotic regime. Leveraging tools from the theory of random processes and concentration of measure, she pursues fundamental insight into modern delay-constrained communication systems.

Research Group
Beverley J. McKeon

Theodore von Karman Professor of Aeronautics

Professor McKeon explores new ways to manipulate or control the boundary layer—the thin layer between a material and flowing air—to improve flow characteristics, such as a reduction of drag, noise, and structural loading or expansion of vehicle performance envelopes during travel. The unifying theme to her work is an experimental and theoretical approach at the intersection of fluid mechanics, control, and materials science to investigate fundamental flow questions, address efficiency and performance challenges in aerospace vehicle design, and respond to the energy conservation imperative in novel and efficient ways.

Research Group
Pietro Perona

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.

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John P. Preskill

Richard P. Feynman Professor of Theoretical Physics; Allen V.C. Davis and Lenabelle Davis Leadership Chair, Institute for Quantum Science and Technology

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.

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Lulu Qian

Assistant Professor of Bioengineering

The Qian lab is interested in designing and constructing nucleic-acid systems from scratch that exhibit programmable behaviors – at the basic level, such as recognizing molecular events from the environment, processing information, making decisions and taking actions; at the advanced level, such as learning and evolving – to explore the principles of molecular programs that nature creates, to embed control within biochemical systems that directly interact with molecules, and eventually, to re-create synthetic molecular programs that approach the complexity and sophistication of life itself.

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Omer Tamuz

Assistant Professor of Economics and Mathematics

Omer Tamuz's work in Economics focuses on how people learn through social interaction, and on games and strategic behavior in networks. His mathematical interests lie in probability theory, ergodic theory, and their connections to group theory. He has also worked in machine learning and statistics, and in particular in combinatorial statistics, where the estimated parameter takes values in a finite set.

Research Group

Research Faculty

 
Edwin Jimenez

Staff Scientist

Paul Rothemund

Research Professor of Bioengineering, Computing and Mathematical Sciences, and Computation and Neural Systems

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James C. (Clint) Scovel

Research Associate

Emeriti

James L. (Jim) Beck

George W. Housner Professor of Engineering and Applied Science, Emeritus

Professor Beck focuses on the development of theory and algorithms for stochastic system modeling, uncertainty propagation and Bayesian updating of dynamic systems and networks based on sensor data, 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 stochastic predictions of the performance of structural systems under earthquakes, reliability assessment of technological networks, 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, Bayesian compressive sensing, and a stochastic mechanics approach to quantum mechanics.

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Kanianthra M. (Mani) Chandy

Simon Ramo Professor of Computer Science, Emeritus

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.

Donald S. Cohen

Charles Lee Powell Professor of Applied Mathematics, Emeritus

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Alain J. Martin

Professor of Computer Science, Emeritus

Professor Martin focuses on asynchronous VLSI and parallel architecture.

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Carver Mead

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

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