School of Engineering


Showing 1-10 of 11 Results

  • 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

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

    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.

  • Michael Bernstein

    Michael Bernstein

    Assistant Professor of Computer Science

    BioMichael Bernstein is an Assistant Professor of Computer Science at Stanford University, where he is a member of the Human-Computer Interaction group. His research focuses on the design of crowdsourcing and social computing systems. His research has received numerous best paper awards at premier computing venues, and his Ph.D. students have gone on both to industry (e.g., Adobe Research, Facebook Data Science) and faculty positions (e.g., Carnegie Mellon, UC Berkeley). Michael has been recognized as a Robert N. Noyce Family Faculty Scholar, and has received an NSF CAREER award, an Outstanding Academic Title citation from the American Library Association, and an Alfred P. Sloan Fellowship. He 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.

  • 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 the faculty of 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 Algeba: Vectors, Matrices, and Least-Squares (with Lieven Vandenberghe, 2018), Convex Optimization (with Lieven Vandenberghe, 2004), Linear Matrix Inequalities in System and Control Theory (with L. El Ghaoui, E. Feron, and V. 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, given every three years 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, and a member of the US National Academy of Engineering and a foreign member of the Chinese Academy of Engineering. 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."