Stanford University
Showing 1-100 of 762 Results
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Sara Achour
Assistant Professor of Computer Science and of Electrical Engineering
Current Research and Scholarly InterestsI am an Assistant Professor jointly appointed to both the Computer Science and the Electrical Engineering Departments at Stanford University. My research focuses on new techniques and tools, specifically new programming languages, compilers, and runtime systems, that enable end-users to more easily develop computations that exploit the potential of emerging computing platforms that exhibit analog behaviors.
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Phil Adamson
Ph.D. Student in Electrical Engineering, admitted Autumn 2020
BioPhil is an Electrical Engineering PhD student conducting inter-disciplinary medical imaging research in the Radiological Sciences Laboratory in the Stanford Medicine Department of Radiology. His research interests include MR methods for metabolic imaging, particularly Deuterium Metabolic Imaging (DMI), and Deep Learning methods for solving inverse problems in limited data regimes with applications to MRI.
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Maneesh Agrawala
Forest Baskett Professor 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
BioI am a PhD candidate in Electrical Engineering working at Professor Jelena Vuckovic's Nanoscale Quantum Photonics Laboratory. My research interests are computational optimizations of photonic devices and quantum technologies made from nanoscale fabrications.
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Nancy Ammar
Ph.D. Student in Electrical Engineering, admitted Autumn 2021
BioNancy Y. Ammar received her B.Sc. degree (with honors) in electronics and communication engineering from Ain Shams University, Cairo, Egypt, in 2019. In her senior year, she worked as an undergraduate Research Assistant in the Microwaves and Antenna Research Lab at Ain Shams University. She worked as an IC design consultant at Siemens EDA (Mentor Graphics previously).
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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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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 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. -
Craig Barratt
Adjunct Professor, Electrical Engineering
BioActing director of System X and instructor for EE310 in Winter and Spring 2023-24.
I received MSEE and Ph.D. (EE) degrees at Stanford long ago, and a BS (math and physics) and BE (EE) from the University of Sydney, Australia (even longer ago).
After a career in the tech industry at several startups and large companies, I currently serve on a couple of public and private company boards, and I'm on the advisory board of Stanford's Center for Digital Health. I also contribute to some open source projects.
See my bio at https://www.linkedin.com/in/craig-h-barratt. -
Mohsen Bayati
Carl and Marilynn Thoma Professor in the Graduate School of Business and Professor, 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. -
Stacey Bent
Vice Provost, Graduate Education & Postdoc Affairs, Jagdeep & Roshni Singh Professor in the School of Engineering, Professor of Energy Science and Engineering and, 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.
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Nikhil Bhagdikar
Ph.D. Student in Electrical Engineering, admitted Autumn 2014
BioEase of implementation and energy efficiency are critical for modern digital ICs. I am researching techniques to improve energy efficiency without compromising on performance or silicon area, especially for CGRA.
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Emil Biju
Masters Student in Electrical Engineering, admitted Autumn 2023
BioI am an M.S. in Electrical Engineering student at Stanford University and my research interests include interpretable machine learning, deep learning and NLP. For the last 2 years, I have been working at Microsoft as a Data and Applied Scientist in the Cybersecurity research team. Previously, I graduated with a Bachelors degree in Electrical Engineering and a minor in Deep Learning from the Indian Institute of Technology (IIT) Madras. During this time, I pursued research at the intersection of NLP and deep learning that led to publications in top conferences such as ACL, COLING and ALENEX.
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Kwabena Boahen
Professor of Bioengineering and of Electrical Engineering
Current Research and Scholarly InterestsBoahen's group analyzes neural behavior computationally to elucidate principles of neural design at the cellular, circuit, and systems levels; and synthesizes neuromorphic electronic systems that scale energy-use with size as efficiently as the brain does. This interdisciplinary research program bridges neurobiology and medicine with electronics and computer science, bringing together these seemingly disparate fields.
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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
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." -
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. -
Alex Carsello
Ph.D. Student in Electrical Engineering, admitted Autumn 2017
BioAlex is currently a Ph.D. student in Electrical Engineering advised by Mark Horowitz and affiliated with the AHA! Agile Hardware Center. He is interested in reconfigurable computing, domain-specific architectures for image processing, and hardware design methodology. He is currently working within the AHA Agile Hardware Project on a next-generation CGRA (coarse-grained reconfigurable architecture) chip generator. Alex received a B.S. in Electrical and Computer Engineering from Washington University in St. Louis in 2017.
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Hugo Chen
Ph.D. Student in Electrical Engineering, admitted Autumn 2022
BioHugo "Jiun-Yu" Chen is currently pursuing his Ph.D. degree in the Department of Electrical Engineering at Stanford University. He earned his M.S. in Photonics and Optoelectronics from National Taiwan University in 2019 and his B.S. in Materials Science and Engineering from National Dong Hwa University in 2017.
Prior to joining Stanford, Hugo worked as an R&D engineer at Taiwan Semiconductor Manufacturing Company (TSMC) in the High Power Program and Analog Power/RF Specialty Technology from 2019 to 2022. His research experience includes investigating GaN high electron mobility transistors (HEMTs) for high power converter applications, oxide-based thin-film transistors (TFTs) for CMOS inverter applications, and III-V quantum dots molecular beam epitaxy (MBE) material growth.
As the first author, Hugo has published two peer-reviewed journal articles, six conference papers, and one US/KR/TW/CN/DE patent. He is currently advised by Professors H.-S. Philip Wong and Kwabena Boahen, and his research focuses on developing ferroelectric field-effect transistors (FeFETs) for dendritic-centric learning.
In his leisure time, Hugo enjoys biking, playing badminton, and watching dramas. -
Jian Chen
Adjunct Professor, Electrical Engineering
BioRetired executive with 30 years of experience in NOR, 2D NAND and 3D NAND flash memories, in the areas of device physics, process integration, reliability, test & product engineering, memory systems architecture, eco-systems and new business development. With a passion for innovation and practical solutions and teamwork, built multiple teams from ground up including at international sites.
Inventor of >150 US patents and some significant ideals that have been used in over 10 generations of NAND memory chip and systems, such as binary cache for MLC (USP# 5,930,167 ), fast MLC NAND writing method GPW (USP# 6,522,580 and 6,643,188 ), read method to correct cell to cell coupling effect (USP#5,867,429), NAND memory WL air-gap (USP# 7,045,849 ), and highly reliable systems EPWR (USP#8,214,700, 8,386,861 aka EPWR).
Published the paper that coined the term GIDL, and the first paper that identified the physics of the GIDL current as due to band-to-band tunneling.
Google scholar h-index 57. -
Po-Han Chen
Ph.D. Student in Electrical Engineering, admitted Winter 2021
BioPo-Han Chen is an EE Ph.D. student at Stanford University supervised by Prof. Priyanka Raina. He received his B.S. in Electrical Engineering and Computer Science (EECS) and M.S. in Electrical Engineering from National Tsing Hua University (Taiwan) in 2016 and 2018 respectively. Before joining Stanford, he was a digital circuit designer at MediaTek where he worked on developing hardware architectures of image processing pipeline. He is interested in designing hardware accelerators. Most of his previous works were related to computational photography algorithms such as digital refocusing. Currently, He is focusing on analyzing and designing architecture of CGRAs to create high-performance, energy-efficient, and reconfigurable computing platforms.
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Bo Wun Cheng
Ph.D. Student in Electrical Engineering, admitted Autumn 2023
BioBo-Wun Cheng is an EE Ph.D. student at Stanford University supervised by Prof. Priyanka Raina. He received his B.S. and M.S. degrees in Computer Science from National Tsing Hua University (Taiwan) in 2021 and 2023, respectively. His current research interest resides in designing and architecting efficient hardware accelerators. Before joining Stanford, his research spans the fields of Graphics Processing Unit memory architecture design and computer vision.
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Dali Cheng
Ph.D. Student in Electrical Engineering, admitted Autumn 2021
Current Research and Scholarly InterestsA light chaser studying photonics from the theoretical perspective. I am devoted to understanding and improving our world using photonic science and engineering.
My current interest includes photonic systems with nontrivial topology, non-Hermiticity, non-Abelian gauge fields, and in the synthetic dimension.
