School of Engineering


Showing 1-100 of 139 Results

  • Maneesh Agrawala

    Maneesh Agrawala

    Forest Baskett Professor in the School of Engineering and Professor, by courtesy, of Electrical Engineering

    Current Research and Scholarly InterestsComputer Graphics, Human Computer Interaction and Visualization.

  • Alex Aiken

    Alex Aiken

    Alcatel-Lucent Professor in Communications and Networking and Professor of Particle Physics and Astrophysics and of Photon Science

    BioAlex Aiken is the Alcatel-Lucent Professor of Computer Science at Stanford. Alex received his Bachelors degree in Computer Science and Music from Bowling Green State University in 1983 and his Ph.D. from Cornell University in 1988. Alex was a Research Staff Member at the IBM Almaden Research Center (1988-1993) and a Professor in the EECS department at UC Berkeley (1993-2003) before joining the Stanford faculty in 2003. His research interest is in areas related to programming languages.

  • Russ B. Altman

    Russ B. Altman

    Kenneth Fong Professor and Professor of Bioengineering, of Genetics, of Medicine (General Medical Discipline), of Biomedical Data Science and, by courtesy, of Computer Science

    Current Research and Scholarly InterestsI refer you to my web page for detailed list of interests, projects and publications. In addition to pressing the link here, you can search "Russ Altman" on http://www.google.com/

  • Peter Bailis

    Peter Bailis

    Assistant Professor of Computer Science

    BioPeter Bailis is an assistant professor of Computer Science at Stanford University. Peter's research in the Future Data Systems group focuses on the design and implementation of next-generation, post-database data-intensive systems. His work spans large-scale data management, distributed protocol design, and architectures for high-volume complex decision support. He is the recipient of an NSF Graduate Research Fellowship, a Berkeley Fellowship for Graduate Study, best-of-conference citations for research appearing in both SIGMOD and VLDB, and the CRA Outstanding Undergraduate Researcher Award. He received a Ph.D. from UC Berkeley in 2015 and an A.B. from Harvard College in 2011, both in Computer Science.

  • Clark Barrett

    Clark Barrett

    Associate Professor (Research) of Computer Science

    Current Research and Scholarly InterestsIn an increasingly automated and networked world, a pressing challenge is ensuring the security and dependability of hardware and software systems. Formal techniques (based on mathematical logic) are among the most powerful tools available for finding difficult bugs and ensuring correctness. My research vision is to develop general-purpose, automated, and scalable formal techniques, with the aim of providing a sound and practical foundation for reliable computer systems.

  • Gill Bejerano

    Gill Bejerano

    Professor of Developmental Biology, of Computer Science, of Pediatrics (Genetics) and of Biomedical Data Science

    Current Research and Scholarly InterestsDr. Bejerano, co-discoverer of ultraconserved elements, studies the Human Genome. His research focuses on genome sequence and function in both humans and related primate, mammalian and vertebrate species. He is deeply interested in mapping both coding and non-coding genome sequence variation to phenotype differences, and in extracting specific genetic insights from high throughput sequencing measurements, in the contexts of development and developmental abnormalities.

  • Frank Bentley

    Frank Bentley

    Lecturer

    BioI am a Distinguished User Researcher at Yahoo in Sunnyvale, CA where I study and create new mobile technologies and applications. Currently I lead user research for our communication products. Work is a fun combination of ethnographic research, prototyping, user studies, and development work which leads us to new product ideas for Yahoo and helps to understand how existing products fit into people's lives. Particular interests lie developing new services to increase feelings of connection in strong-tie social relationships as well as methods for understanding communications needs and rapidly prototyping new concepts for field evaluation.

    I have been teaching since 2006, when I taught my first class on Building Mobile Experiences at MIT. That class ran through 2014 and I moved the class to Stanford in the Spring of 2016. The class also appeared as a MOOC on EdX from 2014-2017, where over 170,000 students from around the world engaged with the course content.

  • Michael Bernstein

    Michael Bernstein

    Associate Professor of Computer Science

    BioMichael Bernstein is an Associate Professor of Computer Science and STMicroelectronics Faculty Scholar at Stanford University, where he is a member of the Human-Computer Interaction group. His research focuses on the design of social computing and crowdsourcing systems. Michael has received eight best paper awards at premier computing venues, and he has been recognized with an NSF CAREER award and an Alfred P. Sloan Fellowship. His Ph.D. students have gone on both to industry (e.g., Adobe Research, Facebook Data Science, entrepreneurship) and faculty careers (e.g., Carnegie Mellon, UC Berkeley). Michael holds a bachelor's degree in Symbolic Systems from Stanford University, as well as a master's degree and a Ph.D. in Computer Science from MIT.

  • Kwabena Boahen

    Kwabena Boahen

    Professor of Bioengineering, of Electrical Engineering and, by courtesy, of Computer Science

    Current Research and Scholarly InterestsLarge-scale models of sensory, perceptual and motor systems

  • Jeannette Bohg

    Jeannette Bohg

    Assistant Professor of Computer Science

    BioJeannette Bohg is an Assistant Professor of Computer Science at Stanford University. She was a group leader at the Autonomous Motion Department (AMD) of the MPI for Intelligent Systems until September 2017. Before joining AMD in January 2012, Jeannette Bohg was a PhD student at the Division of Robotics, Perception and Learning (RPL) at KTH in Stockholm. In her thesis, she proposed novel methods towards multi-modal scene understanding for robotic grasping. She also studied at Chalmers in Gothenburg and at the Technical University in Dresden where she received her Master in Art and Technology and her Diploma in Computer Science, respectively. Her research focuses on perception and learning for autonomous robotic manipulation and grasping. She is specifically interesting in developing methods that are goal-directed, real-time and multi-modal such that they can provide meaningful feedback for execution and learning. Jeannette Bohg has received several awards, most notably the 2019 IEEE International Conference on Robotics and Automation (ICRA) Best Paper Award, the 2019 IEEE Robotics and Automation Society Early Career Award and the 2017 IEEE Robotics and Automation Letters (RA-L) Best Paper Award.

  • Dan Boneh

    Dan Boneh

    Cryptography Professor, Professor of Electrical Engineering and Senior Fellow at the Freeman Spogli Institute for International Studies

    BioProfessor Boneh heads the applied cryptography group and co-direct the computer security lab. Professor Boneh's research focuses on applications of cryptography to computer security. His work includes cryptosystems with novel properties, web security, security for mobile devices, and cryptanalysis. He is the author of over a hundred publications in the field and is a Packard and Alfred P. Sloan fellow. He is a recipient of the 2014 ACM prize and the 2013 Godel prize. In 2011 Dr. Boneh received the Ishii award for industry education innovation. Professor Boneh received his Ph.D from Princeton University and joined Stanford in 1997.

  • Stephen Boyd

    Stephen Boyd

    Samsung Professor in the School of Engineering and Professor, by courtesy, of Computer Science and of Management Science and Engineering

    BioStephen P. Boyd is the Samsung Professor of Engineering, and Professor of Electrical Engineering in the Information Systems Laboratory at Stanford University. He has courtesy appointments in the Department of Management Science and Engineering and the Department of Computer Science, and is member of the Institute for Computational and Mathematical Engineering. His current research focus is on convex optimization applications in control, signal processing, machine learning, and finance.

    Professor Boyd received an AB degree in Mathematics, summa cum laude, from Harvard University in 1980, and a PhD in EECS from U. C. Berkeley in 1985. In 1985 he joined Stanford's Electrical Engineering Department. He has held visiting Professor positions at Katholieke University (Leuven), McGill University (Montreal), Ecole Polytechnique Federale (Lausanne), Tsinghua University (Beijing), Universite Paul Sabatier (Toulouse), Royal Institute of Technology (Stockholm), Kyoto University, Harbin Institute of Technology, NYU, MIT, UC Berkeley, CUHK-Shenzhen, and IMT Lucca. He holds honorary doctorates from Royal Institute of Technology (KTH), Stockholm, and Catholic University of Louvain (UCL).

    Professor Boyd is the author of many research articles and four books: Introduction to Applied Linear Algebra: Vectors, Matrices, and Least-Squares (with Lieven Vandenberghe, 2018), Convex Optimization (with Lieven Vandenberghe, 2004), Linear Matrix Inequalities in System and Control Theory (with El Ghaoui, Feron, and Balakrishnan, 1994), and Linear Controller Design: Limits of Performance (with Craig Barratt, 1991). His group has produced many open source tools, including CVX (with Michael Grant), CVXPY (with Steven Diamond) and Convex.jl (with Madeleine Udell and others), widely used parser-solvers for convex optimization.

    Professor Boyd has received many awards and honors for his research in control systems engineering and optimization, including an ONR Young Investigator Award, a Presidential Young Investigator Award, and the AACC Donald P. Eckman Award. In 2013, he received the IEEE Control Systems Award, given for outstanding contributions to control systems engineering, science, or technology. In 2012, Michael Grant and he were given the Mathematical Optimization Society's Beale-Orchard-Hays Award, for excellence in computational mathematical programming. He is a Fellow of the IEEE, SIAM, and INFORMS, a Distinguished Lecturer of the IEEE Control Systems Society, a member of the US National Academy of Engineering, a foreign member of the Chinese Academy of Engineering, and a foreign member of the National Academy of Engineering of Korea. He has been invited to deliver more than 90 plenary and keynote lectures at major conferences in control, optimization, signal processing, and machine learning.

    He has developed and taught many undergraduate and graduate courses, including Signals & Systems, Linear Dynamical Systems, Convex Optimization, and a recent undergraduate course on Matrix Methods. His graduate convex optimization course attracts around 300 students from more than 20 departments. In 1991 he received an ASSU Graduate Teaching Award, and in 1994 he received the Perrin Award for Outstanding Undergraduate Teaching in the School of Engineering. In 2003, he received the AACC Ragazzini Education award, for contributions to control education, with citation: “For excellence in classroom teaching, textbook and monograph preparation, and undergraduate and graduate mentoring of students in the area of systems, control, and optimization.” In 2016 he received the Walter J. Gores award, the highest award for teaching at Stanford University. In 2017 he received the IEEE James H. Mulligan, Jr. Education Medal, for a career of outstanding contributions to education in the fields of interest of IEEE, with citation "For inspirational education of students and researchers in the theory and application of optimization."

  • Moses Charikar

    Moses Charikar

    Donald E. Knuth Professor and Professor, by courtesy, of Mathematics

    Current Research and Scholarly InterestsApproximation algorithms for discrete optimization problems with provable guarantees; convex optimization approaches for non-convex combinatorial optimization problems; efficient algorithmic techniques for processing, searching and indexing massive high-dimensional data sets; efficient algorithms for computational problems in high-dimensional statistics and optimization problems in machine learning; low-distortion embeddings of finite metric spaces.

  • William Dally

    William Dally

    Professor (Research) of Computer Science and of Electrical Engineering

    BioDally develops efficient hardware for demanding information processing problems and sustainable energy systems. His current projects include domain-specific accelerators for deep learning, bioinformatics, and SAT solving; redesigning memory systems for the data center; developing efficient methods for video perception; and developing efficient sustainable energy systems. His research involves demonstrating novel concepts with working systems. Previous systems include the MARS Hardware Accelerator, the Torus Routing Chip, the J-Machine, M-Machine, the Reliable Router, the Imagine signal and image processor, the Merrimac supercomputer, and the ELM embedded processor. His work on stream processing led to GPU computing. His group has pioneered techniques including fast capability-based addressing, processor coupling, virtual channel flow control, wormhole routing, link-level retry, message-driven processing, deadlock-free routing, pruning neural networks, and quantizing neural networks.

  • David Dill

    David Dill

    Donald E. Knuth Professor in the School of Engineering, Emeritus

    Current Research and Scholarly InterestsSecure and reliable blockchain technology at Facebook.

  • Ron Dror

    Ron Dror

    Associate Professor of Computer Science and, by courtesy, of Molecular and Cellular Physiology and of Structural Biology

    Current Research and Scholarly InterestsMy lab’s research focuses on computational biology, with an emphasis on 3D molecular structure. We combine two approaches: (1) Bottom-up: given the basic physics governing atomic interactions, use simulations to predict molecular behavior; (2) Top-down: given experimental data, use machine learning to predict molecular structures and properties. We collaborate closely with experimentalists and apply our methods to the discovery of safer, more effective drugs.

  • Zakir Durumeric

    Zakir Durumeric

    Assistant Professor of Computer Science

    BioI am an Assistant Professor of Computer Science at Stanford University, where my research broadly focuses on security, networking, and Internet measurement. I am particularly interested in building systems to collect Internet data and using that data to better understand and improve user security and privacy.

  • Dawson Engler

    Dawson Engler

    Associate Professor of Computer Science and of Electrical Engineering

    BioEngler's research focuses both on building interesting software systems and on discovering and exploring the underlying principles of all systems.

  • Stefano Ermon

    Stefano Ermon

    Assistant Professor of Computer Science and Center Fellow, by courtesy, at the Woods Institute for the Environment

    BioI am an Assistant Professor in the Department of Computer Science at Stanford University, where I am affiliated with the Artificial Intelligence Laboratory and a fellow of the Woods Institute for the Environment.

    My research is centered on techniques for scalable and accurate inference in graphical models, statistical modeling of data, large-scale combinatorial optimization, and robust decision making under uncertainty, and is motivated by a range of applications, in particular ones in the emerging field of computational sustainability.

  • Kayvon Fatahalian

    Kayvon Fatahalian

    Assistant Professor of Computer Science

    BioKayvon Fatahalian is an assistant professor of Computer Science at Stanford University. His students work on visual computing systems projects, including large-scale video analytics, programming systems for video data mining, compilation techniques for optimizing image processing pipelines, and systems for real-time 3D graphics.

  • Ron Fedkiw

    Ron Fedkiw

    Professor of Computer Science

    BioFedkiw's research is focused on the design of new computational algorithms for a variety of applications including computational fluid dynamics, computer graphics, and biomechanics.

  • Richard Fikes

    Richard Fikes

    Professor (Research) of Computer Science, Emeritus

    BioRichard Fikes has a long and distinguished record as an innovative leader in the development of techniques for effectively representing and using knowledge in computer systems. He is best known as co-developer of the STRIPS automatic planning system, KIF (Knowledge Interchange Format), the Ontolingua ontology representation language and Web-based ontology development environment, the OKBC (Open Knowledge Base Connectivity) API for knowledge servers, and IntelliCorp's KEE system. At Stanford, he led projects focused on developing large-scale distributed repositories of computer-interpretable knowledge, collaborative development of multi-use ontologies, enabling technology for the Semantic Web, reasoning methods applicable to large-scale knowledge bases, and knowledge-based technology for intelligence analysts. He was principal investigator of major projects for multiple Federal Government agencies including the Defense Advanced Research Projects Agency (DARPA) and the Intelligence Community’s Advanced Research and Development Activity (ARDA).

  • Chelsea Finn

    Chelsea Finn

    Assistant Professor of Computer Science and of Electrical Engineering

    BioChelsea Finn is an Assistant Professor in Computer Science and Electrical Engineering at Stanford University. Professor Finn's research interests lie in the ability to enable robots and other agents to develop broadly intelligent behavior through learning and interaction. Her work lies at the intersection of machine learning and robotic control, including topics such as end-to-end learning of visual perception and robotic manipulation skills, deep reinforcement learning of general skills from autonomously collected experience, and meta-learning algorithms that can enable fast learning of new concepts and behaviors.
    Professor Finn received her Bachelors degree in Electrical Engineering and Computer Science at MIT and her PhD in Computer Science at UC Berkeley. Her research has been recognized through the ACM doctoral dissertation award, an NSF graduate fellowship, a Facebook fellowship, the C.V. Ramamoorthy Distinguished Research Award, and the MIT Technology Review 35 under 35 Award, and her work has been covered by various media outlets, including the New York Times, Wired, and Bloomberg. Throughout her career, she has sought to increase the representation of underrepresented minorities within CS and AI by developing an AI outreach camp at Berkeley for underprivileged high school students, a mentoring program for underrepresented undergraduates across three universities, and leading efforts within the WiML and Berkeley WiCSE communities of women researchers.

    Website: https://ai.stanford.edu/~cbfinn

  • Sean Follmer

    Sean Follmer

    Assistant Professor of Mechanical Engineering and, by courtesy, of Computer Science

    Current Research and Scholarly InterestsHuman Computer Interaction, Haptics, Robotics, Human Centered Design

  • Michael Genesereth

    Michael Genesereth

    Associate Professor of Computer Science

    BioGenesereth is best known for his work on computational logic and applications of that work in enterprise management and electronic commerce. Basic research interests include knowledge representation, automated reasoning, and rational action. Current projects include logical spreadsheets, data, and service integration on the World Wide Web, and computational law.

  • Ashish Goel

    Ashish Goel

    Professor of Management Science and Engineering and, by courtesy, of Computer Science

    BioAshish Goel is a Professor of Management Science and Engineering and (by courtesy) Computer Science at Stanford University. He received his PhD in Computer Science from Stanford in 1999, and was an Assistant Professor of Computer Science at the University of Southern California from 1999 to 2002. His research interests lie in the design, analysis, and applications of algorithms.

  • Sharad Goel

    Sharad Goel

    Assistant Professor of Management Science and Engineering and, by courtesy, of Computer Science, of Sociology and of Law

    BioSharad's primary area of research is computational social science, an emerging discipline at the intersection of computer science, statistics, and the social sciences. He's particularly interested in applying modern computational and statistical techniques to study social and political policies, such as stop-and-frisk, swing voting, filter bubbles, do-not-track, and media bias. Before joining Stanford, Sharad was a senior researcher at Microsoft Research and Yahoo Labs.

  • Christopher Gregg

    Christopher Gregg

    Lecturer

    BioChris Gregg received his Ph.D. in Computer Engineering from the University of Virginia in 2012, has a Master's of Education from Harvard University (2002), and a BS in Electrical Engineering from Johns Hopkins University (1994). Prior to becoming a lecturer at Stanford, Chris was a lecturer in the computer science department at Tufts University, and prior to that he taught high school physics in Massachusetts and California for seven years. Chris was on active duty in the Navy for seven years, and remains as a Commander in the Navy Reserves in the Information Warfare / Cryptology community.

    Chris's research interests include computer architecture (specifically, general purpose computing on GPUs) and the pedagogy of computer science teaching and instruction.

  • Leonidas Guibas

    Leonidas Guibas

    Paul Pigott Professor in the School of Engineering and Professor, by courtesy, of Electrical Engineering

    Current Research and Scholarly InterestsGeometric and topological data analysis and machine learning. Algorithms for the joint analysis of collections of images, 3D models, or trajectories. 3D reconstruction.

  • Nicholas Haber

    Nicholas Haber

    Assistant Professor of Education and, by courtesy, of Computer Science

    Current Research and Scholarly InterestsI use AI models of of exploratory and social learning in order to better understand early human learning and development, and conversely, I use our understanding of early human learning to make robust AI models that learn in exploratory and social ways. Based on this, I develop AI-powered learning tools for children, geared in particular towards the education of those with developmental issues such as the Autism Spectrum Disorder and Attention Deficit Hyperactivity Disorder, in the mold of my work on the Autism Glass Project. My formal graduate training in pure mathematics involved extending partial differential equation theory in cases involving the propagation of waves through complex media such as the space around a black hole. Since then, I have transitioned to the use of machine learning in developing both learning tools for children with developmental disorders and AI and cognitive models of learning.

  • Pat Hanrahan

    Pat Hanrahan

    Canon USA Professor in the School of Engineering and Professor of Electrical Engineering

    BioProfessor Hanrahan's current research involves rendering algorithms, high performance graphics architectures, and systems support for graphical interaction. He also has worked on raster graphics systems, computer animation and modeling and scientific visualization, in particular, volume rendering.

  • Patrick Hayden

    Patrick Hayden

    Stanford Professor of Quantum Physics and Professor, by courtesy, of Computer Science

    BioProfessor Hayden is a leader in the exciting new field of quantum information science. He has contributed greatly to our understanding of the absolute limits that quantum mechanics places on information processing, and how to exploit quantum effects for computing and other aspects of communication. He has also made some key insights on the relationship between black holes and information theory.

  • John Hennessy

    John Hennessy

    President Emeritus, Shriram Family Director of the Knight-Hennessy Scholars Program and Professor of Electrical Engineering and of Computer Science

    BioJohn L. Hennessy joined Stanford’s faculty in 1977 as an assistant professor of electrical engineering. He rose through the academic ranks to full professorship in 1986 and was the inaugural Willard R. and Inez Kerr Bell Professor of Electrical Engineering and Computer Science from 1987 to 2004.

    From 1983 to 1993, Dr. Hennessy was director of the Computer Systems Laboratory, a research and teaching center operated by the Departments of Electrical Engineering and Computer Science that fosters research in computer systems design. He served as chair of computer science from 1994 to 1996 and, in 1996, was named dean of the School of Engineering. As dean, he launched a five-year plan that laid the groundwork for new activities in bioengineering and biomedical engineering. In 1999, he was named provost, the university’s chief academic and financial officer. As provost, he continued his efforts to foster interdisciplinary activities in the biosciences and bioengineering and oversaw improvements in faculty and staff compensation. In October 2000, he was inaugurated as Stanford University’s 10th president, a position he held until 2016. In 2016, he cofounded the Knight-Hennessy Scholars Program, which provides scholarships and leadership development for a global community of scholars enrolled in graduate programs at Stanford. The program admitted it's first class in 2018 and will provide full scholarships for up to 100 100 students every year.

    A pioneer in computer architecture, in 1981 Dr. Hennessy drew together researchers to focus on a computer architecture known as RISC (Reduced Instruction Set Computer), a technology that has revolutionized the computer industry by increasing performance while reducing costs. In addition to his role in the basic research, Dr. Hennessy helped transfer this technology to industry. In 1984, he cofounded MIPS Computer Systems, now MIPS Technologies, which designs microprocessors. In recent years, his research has focused on the architecture of high-performance computers.

    Dr. Hennessy is a recipient of the 2000 IEEE John von Neumann Medal, the 2000 ASEE Benjamin Garver Lamme Award, the 2001 ACM Eckert-Mauchly Award, the 2001 Seymour Cray Computer Engineering Award, a 2004 NEC C&C Prize for lifetime achievement in computer science and engineering, a 2005 Founders Award from the American Academy of Arts and Sciences and the 2012 IEEE Medal of Honor, IEEE's highest award. He is a member of the National Academy of Engineering and the National Academy of Sciences, and he is a fellow of the American Academy of Arts and Sciences, the Association for Computing Machinery, and the Institute of Electrical and Electronics Engineers.

    He has lectured and published widely and is the co-author of two internationally used undergraduate and graduate textbooks on computer architecture design. Dr. Hennessy earned his bachelor’s degree in electrical engineering from Villanova University and his master’s and doctoral degrees in computer science from the State University of New York at Stony Brook.

  • Mark Horowitz

    Mark Horowitz

    Yahoo! Founders Professor in the School of Engineering and Professor of Computer Science

    BioProfessor Horowitz initially focused on designing high-performance digital systems by combining work in computer-aided design tools, circuit design, and system architecture. During this time, he built a number of early RISC microprocessors, and contributed to the design of early distributed shared memory multiprocessors. In 1990, Dr. Horowitz took leave from Stanford to help start Rambus Inc., a company designing high-bandwidth memory interface technology. After returning in 1991, he research group pioneered many innovations in high-speed link design, and many of today’s high speed link designs are designed by his former students or colleagues from Rambus.

    In the 2000s he started a long collaboration with Prof Levoy on computation photography, that included work that led to the Lytro camera. Dr. Horowitz's current research interests are quite broad and span using EE and CS analysis methods to problems in neuro and molecular biology to creating new agile design methodologies for analog and digital VLSI circuits. He remains interested in learning new things, and building interdisciplinary teams.

  • Doug James

    Doug James

    Professor of Computer Science and, by courtesy, of Music

    Current Research and Scholarly InterestsComputer graphics & animation, physics-based sound synthesis, computational physics, haptics, reduced-order modeling

  • Ramesh Johari

    Ramesh Johari

    Professor of Management Science and Engineering and, by courtesy, of Electrical Engineering and of Computer Science

    BioJohari is broadly interested in the design, economic analysis, and operation of online platforms, as well as statistical and machine learning techniques used by these platforms (such as search, recommendation, matching, and pricing algorithms).

  • Sachin Katti

    Sachin Katti

    Associate Professor of Electrical Engineering and of Computer Science

    BioSachin Katti is currently an Assistant Professor of Electrical Engineering and Computer Science at Stanford University. He recently received his PhD in EECS from MIT in 2009. His research focuses on designing and building next generation high capacity wireless networks using techniques from information and coding theory. His dissertation research focused on redesigning wireless mesh networks with network coding as the central unifying design paradigm. The dissertation won the 2008 ACM Doctoral Dissertation Award - Honorable Mention, the George Sprowls Award for Best Doctoral Dissertation in EECS at MIT. His work on network coding was also awarded a MIT Deshpande Center Innovation Grant, and won the 2009 William Bennett Prize for Best Paper in IEEE/ACM Transactions on Networking. His research interests are in networks, wireless communications, applied coding theory and security.

  • Oussama Khatib

    Oussama Khatib

    Weichai Professor and Professor, by courtesy, of Mechanical Engineering and of Electrical Engineering

    BioRobotics research on novel control architectures, algorithms, sensing, and human-friendly designs for advanced capabilities in complex environments. With a focus on enabling robots to interact cooperatively and safely with humans and the physical world, these studies bring understanding of human movements for therapy, athletic training, and performance enhancement. Our work on understanding human cognitive task representation and physical skills is enabling transfer for increased robot autonomy. With these core capabilities, we are exploring applications in healthcare and wellness, industry and service, farms and smart cities, and dangerous and unreachable settings -- deep in oceans, mines, and space.

  • Fredrik Kjolstad

    Fredrik Kjolstad

    Assistant Professor of Computer Science

    BioFredrik Kjolstad is an assistant professor at Stanford University and works on topics in compilers and programming models. He is particularly interested in how we can build programming systems for sparse computing applications, for example in data analytics, computational engineering, and science. He received his PhD from MIT, his master’s degree from the University of Illinois at Urbana-Champaign, and his bachelor’s degree from the Norwegian University of Science and Technology in Gjøvik.

    Website: https://fredrikbk.com/

  • Donald Knuth

    Donald Knuth

    Fletcher Jones Professor of Computer Science, Emeritus

    BioDonald Ervin Knuth is an American computer scientist, mathematician, and Professor Emeritus at Stanford University.

    He is the author of the multi-volume work The Art of Computer Programming and has been called the "father" of the analysis of algorithms. He contributed to the development of the rigorous analysis of the computational complexity of algorithms and systematized formal mathematical techniques for it. In the process he also popularized the asymptotic notation. In addition to fundamental contributions in several branches of theoretical computer science, Knuth is the creator of the TeX computer typesetting system, the related METAFONT font definition language and rendering system, and the Computer Modern family of typefaces.

    As a writer and scholar,[4] Knuth created the WEB and CWEB computer programming systems designed to encourage and facilitate literate programming, and designed the MIX/MMIX instruction set architectures. As a member of the academic and scientific community, Knuth is strongly opposed to the policy of granting software patents. He has expressed his disagreement directly to the patent offices of the United States and Europe. (via Wikipedia)

  • Mykel Kochenderfer

    Mykel Kochenderfer

    Associate Professor of Aeronautics and Astronautics and, by courtesy, of Computer Science

    BioMykel Kochenderfer is Assistant Professor of Aeronautics and Astronautics at Stanford University. Prior to joining the faculty, he was at MIT Lincoln Laboratory where he worked on airspace modeling and aircraft collision avoidance, with his early work leading to the establishment of the ACAS X program. He received a Ph.D. from the University of Edinburgh and B.S. and M.S. degrees in computer science from Stanford University. Prof. Kochenderfer is the director of the Stanford Intelligent Systems Laboratory (SISL), conducting research on advanced algorithms and analytical methods for the design of robust decision making systems. Of particular interest are systems for air traffic control, unmanned aircraft, and other aerospace applications where decisions must be made in uncertain, dynamic environments while maintaining safety and efficiency. Research at SISL focuses on efficient computational methods for deriving optimal decision strategies from high-dimensional, probabilistic problem representations. He is the author of "Decision Making under Uncertainty: Theory and Application" and "Algorithms for Optimization", both from MIT Press. He is a third generation pilot.

  • Christoforos Kozyrakis

    Christoforos Kozyrakis

    Professor of Electrical Engineering and of Computer Science

    BioChristos Kozyrakis research focuses on making computer system of any size faster, cheaper, and greener. His current work focuses on the hardware architecture, runtime environment, programming models, and security infrastructure for warehouse-scale data centers and many-core chips with thousands of general purpose cores and fixed functions accelerators.

  • Anshul Kundaje

    Anshul Kundaje

    Assistant Professor of Genetics and of Computer Science

    Current Research and Scholarly InterestsWe develop statistical and machine learning frameworks to learn predictive, dynamic and causal models of gene regulation from heterogeneous functional genomics data.

  • Monica Lam

    Monica Lam

    Professor of Computer Science, & by courtesy, of Electrical Engineering

    BioDr. Monica Lam is a Professor in the Computer Science Department at Stanford University, and the Faculty Director of the Stanford MobiSocial Laboratory. Dr. Monica Lam obtained her BS degree in computer science from University of British Columbia, and her PhD degree in computer science from Carnegie Mellon University in 1987. She joined Stanford in 1988.

    Professor Lam’s research mission is to disrupt the status quo where centralized monopoly platforms are prevalent and consumers privacy is compromised. This challenging problem led her to ten years of research in many disciplines in computer science: natural language processing, machine learning, compilers, distributed systems, and human-computer interaction. She advocates the development of open-source virtual assistants that users can “program” in natural language; these assistants should be federated to give users choice and to support sharing without a centralized third party. Her research prototype demonstrates a viable open-source alternative to the emerging oligopoly of virtual assistants.

    Prof. Lam is also an expert in compilers for high-performance machines. Her pioneering work of affine partitioning provides a unifying theory to the field of loop transformations for parallelism and locality. Her software pipelining algorithm is used in commercial systems for instruction level parallelism. Her research team created the first, widely adopted research compiler, SUIF. She is a co-author of the classic compiler textbook, popularly known as the “dragon book”.

    Dr. Lam is a Member of the National Academy of Engineering and an Association of Computing Machinery (ACM) Fellow.

  • James Landay

    James Landay

    Anand Rajaraman and Venky Harinarayan Professor in the School of Engineering

    Current Research and Scholarly InterestsLanday's current research interests include Technology to Support Behavior Change (especially for health and sustainability), Crowdsourcing, Demonstrational User Interfaces, Mobile & Ubiquitous Computing, Cross-Cultural Interface Design, and User Interface Design Tools. He has developed tools, techniques, and a top professional book on Web Interface Design.

    Dr. Landay is the founder and co-director of the World Lab, a joint research and educational effort with Tsinghua University in Beijing.

  • Cynthia Lee

    Cynthia Lee

    Senior Lecturer of Computer Science

    Current Research and Scholarly InterestsI have a PhD in Computer Science from the University of California, San Diego, in the area of High-Performance Computing (HPC), specifically market-based scheduling algorithms. My graduate research was done as part of San Diego Supercomputer Center (SDSC)'s Performance Modeling and Characterization Lab (PMaC), where I investigated economic models of scheduling on high performance computing systems. My adviser was Allan Snavely of SDSC.

    My dissertation abstract is as follows: Effective management of Grid and HPC resources is essential to maximizing return on the substantial infrastructure investment these resources entail. An important prerequisite to effective resource management is productive interaction between the user and scheduler. My work analyzes several aspects of the user-scheduler relationship and develops solutions to three of the most vexing barriers between the two. First, users' monetary valuation of compute time and schedule turnaround time is examined in terms of a utility function. Second, responsiveness of the scheduler to users' varied valuations is optimized via a genetic algorithm heuristic, creating a controlled market for computation. Finally, the chronic problem of inaccurate user runtime requests, and its implications for scheduler performance, is examined, along with mitigation techniques.

    My current research projects are in the area of Computer Science Education, with an emphasis on assessment and the use of Peer Instruction pedagogy in lecture. With colleagues Mark Guzdial, Leo Porter, and Beth Simon, I run the New CS Faculty Teaching Workshop, an annual "bootcamp" on how to teach effectively that draws attendees from dozens of the top CS programs in the country. The short-term goal is to give newly-hired faculty entering their first year of teaching the skills they need to succeed for themselves and their students. The long-term goal is to transform undergraduate education in CS by seeding our best rising stars with best practices so they can create communities of practice as their institutions and mentor their students in active learning strategies, creating a culture where these are the new norm.

  • Jurij Leskovec

    Jurij Leskovec

    Associate Professor of Computer Science

    BioLeskovec's research focuses on the analyzing and modeling of large social and information networks as the study of phenomena across the social, technological, and natural worlds. He focuses on statistical modeling of network structure, network evolution, and spread of information, influence and viruses over networks. Problems he investigates are motivated by large scale data, the Web and other on-line media. He also does work on text mining and applications of machine learning.

  • Philip Levis

    Philip Levis

    Associate Professor of Computer Science and of Electrical Engineering

    BioProfessor Levis' research focuses on the design and implementation of efficient software systems for embedded wireless sensor networks; embedded network sensor architecture and design; systems programming and software engineering.

  • Michael Levitt

    Michael Levitt

    Robert W. and Vivian K. Cahill Professor in Cancer Research in the School of Medicine and Professor, by courtesy, of Computer Science

    Current Research and Scholarly InterestsStanford Professor of Biophysics and Computational Biology, Cambridge PhD and DSc, 2013 Chemistry Nobel Laureate (complex systems), FRS & US National Academy member, I code well for my age.

  • Marc Levoy

    Marc Levoy

    VMware Founders Professor in Computer Science and Professor of Electrical Engineering, Emeritus

    BioLevoy's current interests include the science and art of photography, computational photography, light field sensing and display, and applications of computer graphics in microscopy and biology.

  • Percy Liang

    Percy Liang

    Associate Professor of Computer Science and, by courtesy, of Statistics

    BioPercy Liang is an Associate Professor of Computer Science at Stanford University (B.S. from MIT, 2004; Ph.D. from UC Berkeley, 2011). His two research goals are (i) to make machine learning more robust, fair, and interpretable; and (ii) to make computers easier to communicate with through natural language. His awards include the Presidential Early Career Award for Scientists and Engineers (2019), IJCAI Computers and Thought Award (2016), an NSF CAREER Award (2016), a Sloan Research Fellowship (2015), and a Microsoft Research Faculty Fellowship (2014).

  • C. Karen Liu

    C. Karen Liu

    Associate Professor of Computer Science

    BioC. Karen Liu is an associate professor in the Computer Science Department at Stanford University. Prior to joining Stanford, Liu was a faculty member at the School of Interactive Computing at Georgia Tech. She received her Ph.D. degree in Computer Science from the University of Washington. Liu's research interests are in computer graphics and robotics, including physics-based animation, character animation, optimal control, reinforcement learning, and computational biomechanics. She developed computational approaches to modeling realistic and natural human movements, learning complex control policies for humanoids and assistive robots, and advancing fundamental numerical simulation and optimal control algorithms. The algorithms and software developed in her lab have fostered interdisciplinary collaboration with researchers in robotics, computer graphics, mechanical engineering, biomechanics, neuroscience, and biology. Liu received a National Science Foundation CAREER Award, an Alfred P. Sloan Fellowship, and was named Young Innovators Under 35 by Technology Review. In 2012, Liu received the ACM SIGGRAPH Significant New Researcher Award for her contribution in the field of computer graphics.

  • Christopher Manning

    Christopher Manning

    Thomas M. Siebel Professor in Machine Learning, Professor of Linguistics and of Computer Science

    BioChristopher Manning is a professor of computer science and linguistics at Stanford University, Director of the Stanford Artificial Intelligence Laboratory, and Co-director of the Stanford Human-Centered Artificial Intelligence Institute. He works on software that can intelligently process, understand, and generate human language material. He is a leader in applying Deep Learning to Natural Language Processing, including exploring Tree Recursive Neural Networks, neural network dependency parsing, the GloVe model of word vectors, neural machine translation, question answering, and deep language understanding. He also focuses on computational linguistic approaches to parsing, natural language inference and multilingual language processing, including being a principal developer of Stanford Dependencies and Universal Dependencies. Manning is an ACM Fellow, a AAAI Fellow, an ACL Fellow, and a Past President of ACL. He has coauthored leading textbooks on statistical natural language processing and information retrieval. He is the founder of the Stanford NLP group (@stanfordnlp) and manages development of the Stanford CoreNLP software.

  • David Mazieres

    David Mazieres

    Professor of Computer Science

    BioMazieres investigates ways to improve the security of operating systems, file systems, and distributed systems. In addition, he has worked on large-scale peer-to-peer systems and e-mail privacy.

  • Nick McKeown

    Nick McKeown

    Kleiner Perkins, Mayfield, and Sequoia Capital Professor in the School of Engineering and Professor of Computer Science

    BioMcKeown researches techniques to improve the Internet. Most of this work has focused on the architecture, design, analysis, and implementation of high-performance Internet switches and routers. More recently, his interests have broadened to include network architecture, backbone network design, congestion control; and how the Internet might be redesigned if we were to start with a clean slate.

  • John Mitchell

    John Mitchell

    Mary and Gordon Crary Family Professor in the School of Engineering, and Professor, by courtesy, of Electrical Engineering and of Education

    BioComputer security: access control, network protocols, and software system security. Programming languages, type systems, object systems, and formal methods. Applications of mathematical logic to computer science.

  • Juan Carlos Niebles Duque

    Juan Carlos Niebles Duque

    Sr Res Engineer

    Current Research and Scholarly InterestsThe goal of my research is to enable computers and robots to perceive the visual world by developing novel computer vision algorithms for automatic analysis of images and videos. We tackle fundamental open problems in computer vision research related to the visual recognition and understanding of human actions and activities, objects, scenes, and events. We also develop systems that solve practical world problems by introducing cutting-edge computer vision technologies into new domains.

  • Aina Niemetz

    Aina Niemetz

    Research Engineer

    Biohttps://cs.stanford.edu/people/niemetz

  • Kunle Olukotun

    Kunle Olukotun

    Cadence Design Systems Professor and Professor of Electrical Engineering

    BioKunle Olukotun is the Cadence Design Systems Professor in the School of Engineering and Professor of Electrical Engineering and Computer Science at Stanford University. Olukotun is well known as a pioneer in multicore processor design and the leader of the Stanford Hydra chip multiprocessor (CMP) research project. Olukotun founded Afara Websystems to develop high-throughput, low-power multicore processors for server systems. The Afara multicore processor, called Niagara, was acquired by Sun Microsystems. Niagara derived processors now power all Oracle SPARC-based servers. Olukotun currently directs the Stanford Pervasive Parallelism Lab (PPL), which seeks to proliferate the use of heterogeneous parallelism in all application areas using Domain Specific Languages (DSLs).

  • John Ousterhout

    John Ousterhout

    Leonard Bosack and Sandy Lerner Professor in the School of Engineering

    Current Research and Scholarly InterestsOusterhout's research ranges across a variety of topics in system software, software development tools, and user interfaces. His current research is in the area of granular computing: new software stack layers that allow the execution of large numbers of very small tasks (as short as a few microseconds) in a datacenter. Current projects are developing new techniques for thread management, network communication, and logging.

  • Andreas Paepcke

    Andreas Paepcke

    Sr. Research Engineer

    BioDr. Andreas Paepcke is a Senior Research Scientist and Director for Data Analytics in support of online teaching efforts at Stanford University. His interests include user interfaces and systems for teaching and learning. He uses data analytics to create tools that benefit these online efforts. In the past Dr. Paepcke and his groups of students designed and implemented WebBase, an experimental storage and high speed dissemination system for Web content. Their work on small devices focused on novel methods for summarizing and transforming Web pages, and browsing images on small displays. Dr. Paepcke has served on numerous program committees, including a position as Vice Program Chair, heading the World-Wide Web Conference's 'Browsers and User Interfaces' program track, and as Program Chair for the Joint Conference on Digital Libraries 2008. He served on several National Science Foundation proposal evaluation panels and was co-founding associate editor of ACM Transactions on the Web. Dr. Paepcke received BS and MS degrees in applied mathematics from Harvard University, and a Ph.D. in Computer Science from the University of Karlsruhe, Germany. Previously, he worked as a researcher at Hewlett-Packard Laboratory, and as a research consultant at Xerox PARC. He has served on a number of technical advisory boards for startup companies.

  • Marco Patrignani

    Marco Patrignani

    Visiting Asst Prof

    Current Research and Scholarly InterestsFoundations of programming languages, PL security, secure compilation

  • Marco Pavone

    Marco Pavone

    Associate Professor of Aeronautics and Astronautics and, by courtesy, of Electrical Engineering and of Computer Science

    BioDr. Marco Pavone is an Assistant Professor of Aeronautics and Astronautics at Stanford University, where he is the Director of the Autonomous Systems Laboratory and Co-Director of the Center for Automotive Research at Stanford. Before joining Stanford, he was a Research Technologist within the Robotics Section at the NASA Jet Propulsion Laboratory. He received a Ph.D. degree in Aeronautics and Astronautics from the Massachusetts Institute of Technology in 2010. His main research interests are in the development of methodologies for the analysis, design, and control of autonomous systems, with an emphasis on self-driving cars, autonomous aerospace vehicles, and future mobility systems. He is a recipient of several awards, including a Presidential Early Career Award for Scientists and Engineers from President Barack Obama, an ONR Young Investigator Award, an NSF CAREER Award, and a NASA Early Career Faculty Award. He was identified by the American Society for Engineering Education (ASEE) as one of America's 20 most highly promising investigators under the age of 40. His work has been recognized with best paper nominations or awards at the International Conference on Intelligent Transportation Systems, at the Field and Service Robotics Conference, at the Robotics: Science and Systems Conference, and at NASA symposia.

  • Roy Pea

    Roy Pea

    Director, H-STAR, David Jacks Professor of Education and Professor, by courtesy, of Computer Science

    Current Research and Scholarly Interestslearning sciences focus on advancing theories, research, tools and social practices of technology-enhanced learning of complex domains

  • Serge Plotkin

    Serge Plotkin

    Associate Professor of Computer Science, Emeritus

    BioPlotkin's focus is on optimization problems that are encountered in the context of design, management, and maintenance of broadband communication networks. Currently his main effort in this area is concentrated on development of algorithms for network topology design, routing, capacity sizing, server placement, and fair resource allocation. His goal is to develop both offline strategies that can be used during network design stage, as well as online strategies that can be applied to optimize existing network infrastructure.

  • Balaji Prabhakar

    Balaji Prabhakar

    VMware Founders Professor, Professor of Electrical Engineering and, by courtesy, of Operations, Information and Technology at the Graduate School of Business

    BioPrabhakar's research focuses on the design, analysis, and implementation of data networks: both wireline and wireless. He has been interested in designing network algorithms, problems in ad hoc wireless networks, and designing incentive mechanisms. He has a long-standing interest in stochastic network theory, information theory, algorithms, and probability theory.

  • Priyanka Raina

    Priyanka Raina

    Assistant Professor of Electrical Engineering and, by courtesy, of Computer Science

    Current Research and Scholarly InterestsFor Priyanka's research please visit her group research page at https://stanfordaccelerate.github.io

  • Christopher Re

    Christopher Re

    Associate Professor of Computer Science

    Current Research and Scholarly InterestsAlgorithms, systems, and theory for the next generation of data processing and data analytics systems.