School of Engineering
Showing 11-20 of 145 Results
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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. In 2025, he was awarded the IFAC Nathaniel B. Nichols Medal.
He is a Fellow of the IEEE, SIAM, INFORMS, IFAC, and ACA, 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 100 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." -
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. -
E.J. Chichilnisky
John R. Adler Professor, Professor of Neurosurgery and of Ophthalmology and, by courtesy, of Electrical Engineering
Current Research and Scholarly InterestsFunctional circuitry of the retina and design of retinal prostheses
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Joonhee Choi
Assistant Professor of Electrical Engineering
BioJoonhee Choi is an Assistant Professor of Electrical Engineering at Stanford University. Joonhee received his Ph.D. and master’s from Harvard University, as well as master’s and bachelor’s degrees from Korea Advanced Institute of Science & Technology. Prior to joining Stanford, he worked as an IQIM postdoctoral fellow at the Institute for Quantum Information and Matter (IQIM) at Caltech. Joonhee’s research focus has been on engineering the dynamics of quantum many-body systems for both exploring fundamental science and demonstrating practical quantum applications. Throughout his career, he has worked in a wide variety of fields, including nonlinear nano-optics, ultrafast phenomena, solid-state and atomic physics, as well as quantum many-body physics. His expertise extends to practical applications in quantum metrology, communication, and information processing.
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Srabanti Chowdhury
Professor of Electrical Engineering, Senior Fellow at the Precourt Institute for Energy and Professor, by courtesy, of Materials Science and Engineering
Current Research and Scholarly InterestsWide bandap materials & devices for RF, Power and energy efficient electronics
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John M. Cioffi
Hitachi America Professor in the School of Engineering, Emeritus
Current Research and Scholarly InterestsCioffi researches and teaches in the area of digital transmission. He introduced the basic transmission methods that are a foundation for all modern broadband internet connectivity, which corresponding patents are Stanford Engineering's all-time #2 royalty generator (after #1 search engine). Roughly half his career was spent in industry during various periods as Stanford student or faculty. He has been primary advisor for over 90 Stanford PhD students, and taught communications to 1000's.
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Todd Coleman
Associate Professor of Bioengineering and, by courtesy, of Electrical Engineering
BioTodd P. Coleman is an Associate Professor in the Department of Bioengineering, and by courtesy, Electrical Engineering at Stanford University. He received B.S. degrees in electrical engineering (summa cum laude), as well as computer engineering (summa cum laude) from the University of Michigan (Go Blue). He received M.S. and Ph.D. degrees from MIT in electrical engineering and computer science. He did postdoctoral studies at MIT and Mass General Hospital in quantitative neuroscience. He previously was a faculty member in the Departments of Electrical & Computer Engineering and Bioengineering at the University of Illinois, Urbana-Champaign, and the University of California, San Diego, respectively. Dr. Coleman’s research is very multi-disciplinary, using tools from applied probability, physiology, and bioelectronics. Examples include, for instance, optimal transport methods in high-dimensional uncertainty quantification and developing technologies and algorithms to monitor and modulate physiology of the nervous systems in the brain and visceral organs. He has served as a Principal Investigator on grants from the NSF, NIH, Department of Defense, and multiple private foundations. Dr. Coleman is an inventor on 10 granted US patents. He has been selected as a Gilbreth Lecturer for the National Academy of Engineering, a TEDMED speaker, and a Fellow of IEEE as well as the American Institute for Medical and Biological Engineering. He recently served as Chair of the National Academies Standing Committee on Biotechnology Capabilities and National Security Needs.
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Daniel Norbert Congreve
Assistant Professor of Electrical Engineering
BioDan is an Assistant Professor in the Department of Electrical Engineering at Stanford University. Prior to Stanford, Dan received his B.S. and M.S. from Iowa State in 2011, working with Vik Dalal studying defect densities of nano-crystalline and amorphous silicon. He then received his PhD from MIT in Electrical Engineering in 2015, studying under Marc Baldo. His thesis work focused on photonic energy conversion using singlet fission and triplet fusion as downconverting and upconverting processes, respectively. He spent a year as a postdoc with Will Tisdale in Chemical Engineering at MIT studying perovskite nanoplatelets. He joined the Rowland Institute in 2016 as a Rowland Fellow before starting at Stanford in 2020. Dan is a Moore Inventor Fellow, Sloan Research Fellow, Intel Rising Star, and co-founder of Quadratic3D, a startup looking to commercialize 3D printing technologies. His current research interests focus on engineering nanomaterials to solve challenging problems.
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Adam de la Zerda
Associate Professor of Structural Biology and, by courtesy, of Electrical Engineering
Current Research and Scholarly InterestsMolecular imaging technologies for studying cancer biology in vivo
