School of Engineering
Showing 1-6 of 6 Results
Richard W. Weiland Professor in the School of Engineering and Professor of Electrical Engineering
BioNick Bambos is R. Weiland Professor in the School of Engineering at Stanford University, having a joint appointment in the Department of Electrical Engineering and the Department of Management Science & Engineering. He has been the Fortinet Founders Department Chair of the Management Science & Engineering Department (2016 – 20).
He heads the Computer Systems Performance Engineering Lab (Perf-Lab) at Stanford, comprised of doctoral students and industry visitors engaged in various research projects, and was the Director (1999 – 2005) of the Stanford Networking Research Center (a research project of about $30M). He has published over 300 peer-reviewed research publications and graduated over 40 doctoral students (including two post-doctoral ones), who have moved on to leadership positions in academia, the Silicon Valley industries and technology startups, finance and venture capital, etc.
His research interests are in architecture and high-performance engineering of computer systems and networks, as well as data analytics with an emphasis on medical and health-care analytics. His research contributions span the areas of networking and the Internet, cloud computing and data centers, multimedia streaming, computer security, digital health, etc. His methodological interests and contributions span the areas of network control, online task scheduling, routing and distributed processing, machine learning and artificial intelligence, etc.
He received his Ph.D. (1989) in Electrical Engineering & Computer Sciences from the University of California at Berkeley. Before joining Stanford in 1996, he served as assistant professor (1989 – 95) and tenured associate professor (1995 – 96) of Electrical Engineering at the University of California at Los Angeles (UCLA).
He has received several best research paper awards and has been the Cisco Systems Faculty Development Chair and the David Morgenthaler Faculty Scholar at Stanford. He has won the IBM Faculty Award, as well as the National Young Investigator Award and the Research Initiation Award from the National Science Foundation. He has been a Berkeley U.C. Regents Fellow, an E. C. Anthony Fellow, and a D. & S. Gale Fellow.
He has served on various editorial boards of research journals, scientific boards of research labs, international technical and scientific committees, and technical review panels for networking and computing technologies. He has also served on corporate technical boards, as consultant and co-founder of technology start-up companies, and as expert witness in high-profile patent litigation and other legal cases involving information technologies.
Professor of Operations, Information and Technology at the Graduate School of Business and, by courtesy, of Electrical Engineering
Current Research and Scholarly Interests1) Healthcare management: I am interested in improving healthcare delivery using data-driven modeling and decision-making.
2) Network models and message-passing algorithms: I work on graphical modeling ideas motivated from statistical physics and their applications in statistical inference.
3) Personalized decision-making: I work on machine learning and statistical challenges of personalized decision-making. The problems that I have worked on are primarily motivated by healthcare applications.
Vice Provost, Graduate Edu & Postdoc Affairs, Jagdeep & Roshni Singh Professor in the School of Engineering, Professor of Energy Science Eng, Sr Fellow at Precourt & Professor, by courtesy, of Electrical Eng, Materials Sci Eng & Chemistry
BioThe research in the Bent laboratory is focused on understanding and controlling surface and interfacial chemistry and applying this knowledge to a range of problems in semiconductor processing, micro- and nano-electronics, nanotechnology, and sustainable and renewable energy. Much of the research aims to develop a molecular-level understanding in these systems, and hence the group uses of a variety of molecular probes. Systems currently under study in the group include functionalization of semiconductor surfaces, mechanisms and control of atomic layer deposition, molecular layer deposition, nanoscale materials for light absorption, interface engineering in photovoltaics, catalyst and electrocatalyst deposition.
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
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.
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."