School of Engineering
Showing 1-50 of 567 Results
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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.
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Geun Ho Ahn
Ph.D. Student in Electrical Engineering, admitted Autumn 2018
Grader for EE222. Autumn 2019-20., Electrical Engineering - Student ServicesBioI am a PhD candidate in Electrical Engineering at Stanford University. I joined Professor Jelena Vuckovic's Nanoscale Quantum Photonics Lab in 2018, and I am currently working on computational optimizations of photonic devices and quantum technologies made from nanoscale fabrications. I obtained my undergraduate degree in Electrical Engineering and Computer Sciences from University of California, Berkeley.
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Rehman Ali
Ph.D. Student in Electrical Engineering, admitted Autumn 2017
Masters Student in Computational and Mathematical Engineering, admitted Autumn 2017BioRehman Ali received the B.S. degree in biomedical engineering from Georgia Institute of Technology in 2016. He is currently an NDSEG fellow, completing a M.S. in Computational & Mathematical Engineering and pursuing a Ph.D. in Electrical Engineering at Stanford. His research interests include signal processing, inverse problems, computational modeling of acoustics, and real-time beamforming algorithms. His current research is developing accurate and spatially resolved speed-of-sound imaging in tissue based on phase aberration correction, spatial coherence, and computed tomography
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Amin Arbabian
Associate Professor of Electrical Engineering
Current Research and Scholarly InterestsMy group's research covers RF circuits and system design for (1) biomedical, (2) sensing, and (3) Internet of Things (IoT) applications.
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Serhat Arslan
Ph.D. Student in Electrical Engineering, admitted Autumn 2018
Current Research and Scholarly InterestsNetwork intelligence
There are 2 main aspects of network management:
Sensing
- Collecting useful and enough amount of information from the network is essential for modern, data-centric decision processes to work well.
Frameworks such as In-band Network Telemetry could be utilized to collect precise information on every single packet in the network.
Control
- Modern data science methodologies allow engineers to infer about the state of the network.
Naturally, the next step is to design tailored control algorithms that would utilize available resources the best.
Potential methods include, but not limited to, machine learning algorithms and control theory. -
Richard Bahr
Adjunct Professor, Electrical Engineering
BioAcademic experience:
Presently advising the Stanford SystemX Alliance, and the EE/CS AHA! Research center as an adjunct prof. Formerly the executive director of the SystemX Alliance, and a consulting professor at Stanford.
Commercial experience:
Presently an advisor, consultant and mentor to a number of startup companies primarily in the computing and wireless spaces. Formerly the SrVP responsible for Wi-Fi technology at Qualcomm, and before that the engineering executive responsible for the MIPS microprocessor and Cray supercomputer development at SGI.
Education: BSEE and MSEE from MIT.
For more extensive background, please consult my linked in profile: https://www.linkedin.com/in/rickbahr. -
Nicholas Bambos
Richard W. Weiland Professor in the School of Engineering and Professor of Electrical Engineering
BioNick Bambos is a Professor at Stanford University, having a joint appointment in the Department of Electrical Engineering and the Department of Management Science & Engineering. He heads the Network Architecture and Performance Engineering research group at Stanford, conducting research in wireless network architectures, the Internet infrastructure, packet switching, network management and information service engineering, engaged in various projects of his Network Architecture Laboratory (NetLab). His current technology research interests include high-performance networking, autonomic computing, and service engineering. His methodological interests are in network control, online task scheduling, queueing systems and stochastic processing networks.
He has graduated over 20 Ph.D. students, who are now at leadership positions in academia (Stanford, CalTech, Michigan, GaTech, NYU, UBC, etc.) and the information technology industry (Cisco, Broadcom, IBM Labs, Qualcomm, Nokia, MITRE, Sun Labs, ST Micro, Intel, Samsung, TI, etc.) or have become successful entrepreneurs. From 1999 to 2005 he served as the director of the Stanford Networking Research Center, a major partnership/consortium between Stanford and information technology industries, involving tens of corporate members, faculty and doctoral students. He is now heading a new research initiative at Stanford on Networked Information Service Engineering.
He is on the Editorial Boards of several research journals and serves on various international technical committees and review panels for networking research and information technologies. He has been serving on the boards of various start-up companies in the Silicon Valley, consults on high technology development and management matters, and has served as lead expert witness in high-profile patent litigation cases in networking and computing. -
Mohsen Bayati
Associate Professor of Operations, Information and Technology at the Graduate School of Business and, by courtesy, of Electrical Engineering
Current Research and Scholarly InterestsMy main research areas of interest include:
1) Probabilistic and statistical models for decision making with large-scale and complex data (and applications in healthcare).
2) Graphical models and message-passing algorithms. -
Stacey Bent
Vice Provost for Graduate Education and Postdoctoral Affairs, Jagdeep and Roshni Singh Professor in the School of Engineering, and Professor, by courtesy, of Materials Science & Engineering and of Electrical Engineering
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.
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Kwabena Boahen
Professor of Bioengineering and of Electrical Engineering
Current Research and Scholarly InterestsLarge-scale models of sensory, perceptual and motor systems
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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.
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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."
