School of Engineering


Showing 11-20 of 138 Results

  • Stephen Boyd

    Stephen Boyd

    Samsung Professor in the School of Engineering

    BioStephen P. Boyd is the Samsung Professor of Engineering, and Professor of Electrical Engineering in the Information Systems Laboratory at Stanford University, and a 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.

    He 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. In 2023, he was given the AACC Richard E. Bellman Control Heritage Award, the highest recognition of professional achievement for U.S. control systems engineers and scientists. He is a Fellow of the IEEE, SIAM, INFORMS, and IFAC, 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. 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."

  • Leticia Britos Cavagnaro

    Leticia Britos Cavagnaro

    Adjunct Professor

    BioLeticia Britos Cavagnaro, Ph.D., is a scientist turned designer with a knack for creating transformative learning experiences. She holds a Ph.D. in Developmental Biology from Stanford's School of Medicine, and is a former member of the Research in Education & Design Lab (REDlab) from Stanford’s School of Education. She is the co-founder and co-Director of the University Innovation Fellows, a program of the Hasso Plattner Institute of Design (d.school), which empowers students to be co-designers of their education in collaboration with faculty and leaders at their schools. Leticia was the founding Deputy Director of the National Center for Engineering Pathways to Innovation (Epicenter), an NSF-funded initiative that operated from 2011 to 2016 to foster innovation and entrepreneurship in engineering education across the United States. Leticia works with educators from hundreds of schools and across disciplines in transforming their teaching practices by applying design abilities and pedagogical levers through the Teaching and Learning Studio program of the d.school. In addition, she works with corporate, non-profit and education leaders in the US and abroad in exploring how design can embolden leadership and drive responsible innovation. Leticia teaches Advanced Reflective Practice and Capstone Project to graduate students from Stanford’s Design Impact MS program, and uses emerging technologies to empower learners to be self-directed, action-oriented, and reflective shapers of the future. She was born in Uruguay, grew up in Colombia, and lives in San Francisco with her husband.

    Connect with Leticia:
    LinkedIn: linkedin.com/pub/leticia-britos-cavagnaro/9/b4a/752/
    Twitter: @LeticiaBritosC (twitter.com/leticiabritosc)

  • Emmanuel Candes

    Emmanuel Candes

    Barnum-Simons Chair of Math and Statistics, and Professor of Statistics and, by courtesy, of Electrical Engineering

    BioEmmanuel Candès is the Barnum-Simons Chair in Mathematics and Statistics, a professor of electrical engineering (by courtesy) and a member of the Institute of Computational and Mathematical Engineering at Stanford University. Earlier, Candès was the Ronald and Maxine Linde Professor of Applied and Computational Mathematics at the California Institute of Technology. His research interests are in computational harmonic analysis, statistics, information theory, signal processing and mathematical optimization with applications to the imaging sciences, scientific computing and inverse problems. He received his Ph.D. in statistics from Stanford University in 1998.

    Candès has received several awards including the Alan T. Waterman Award from NSF, which is the highest honor bestowed by the National Science Foundation, and which recognizes the achievements of early-career scientists. He has given over 60 plenary lectures at major international conferences, not only in mathematics and statistics but in many other areas as well including biomedical imaging and solid-state physics. He was elected to the National Academy of Sciences and to the American Academy of Arts and Sciences in 2014.

  • Gunnar Carlsson

    Gunnar Carlsson

    Ann and Bill Swindells Professor, Emeritus

    BioDr. Carlsson has been a professor of mathematics at Stanford University since 1991. In the last ten years, he has been involved in adapting topological techniques to data analysis, under NSF funding and as the lead PI on the DARPA “Topological Data Analysis” project from 2005 to 2010. He is the lead organizer of the ATMCS conferences, and serves as an editor of several Mathematics journals

  • Carissa Carter

    Carissa Carter

    Adjunct Professor

    BioCarissa Carter is the Academic Director at the Stanford d.school. In this role she guides the development of the d.school’s pedagogy, leads its instructors, and shapes its class offerings. She teaches courses on the intersection of data and design, design for climate change, design for emerging tech, and maps and the visual sorting of information.

  • John M. Cioffi

    John M. Cioffi

    Hitachi America Professor in the School of Engineering, Emeritus

    BioJohn M. Cioffi teaches Stanford's graduate electrical engineering course sequence in digital communications, part-time as recalled emeritus presently, from 1986 to the present. Cioffi's research interests are in the theory of transmitting the highest possible data rates on a number of different communications channels, many of which efforts spun out of Stanford through he and/or his many former PhD students to companies, most notably including the basic designed globally used 500 million DSL connections. Cioffi also oversaw the prototype developments for the worlds first cable modem and digital-audio broadcast systems. Cioffi pioneering the use of remote management algorithms to improve (over the internet or cloud) both wireline (DSL) and wireless (Wi-Fi) physical-layer transmission performance, an area often known as Dynamic Spectrum Management or Dynamic Line Management. Cioffi is co-inventor on basic patents for vectored DSL transmission and optimized MIMO wireless transmission. In his early career, Cioffi developed the worlds first full-duplex voiceband data modem while at Bell Laboratories, and the worlds first adaptively equalized disk read channel while at IBM. His courses and research projects over the years center on the area of multiuser transmission methods.

  • Eric Darve

    Eric Darve

    Professor of Mechanical Engineering

    Current Research and Scholarly InterestsThe research interests of Professor Darve span across several domains, including machine learning for engineering, surrogate and reduced order modeling, stochastic inversion, anomaly detection for engineering processes and manufacturing, numerical linear algebra, high-performance and parallel computing, and GPGPU.