Electrical Engineering
Showing 701-795 of 795 Results
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Shan X. Wang
Leland T. Edwards Professor in the School of Engineering and Professor of Electrical Engineering and, by courtesy, of Radiology (Molecular Imaging Program at Stanford)
Current Research and Scholarly InterestsShan Wang was named the Leland T. Edwards Professor in the School of Engineering in 2018. He directs the Center for Magnetic Nanotechnology and is a leading expert in Edge AI, biosensors, information storage and spintronics. His research and inventions span across a variety of areas including Edge AI, magnetic biochips, in vitro diagnostics, cancer biomarkers, magnetic nanoparticles, magnetic sensors, magnetoresistive random access memory, and magnetic integrated inductors.
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Itschak Weissman
Robert and Barbara Kleist Professor in the School of Engineering
BioTsachy's research focuses on Information Theory, Data Compression and Communications, Statistical Signal Processing, Machine Learning, the interplay between them, and their applications, with recent focus on applications to genomic data compression and processing. He is inventor of several patents and involved in several companies as member of the technical board. IEEE fellow, he serves on the board of governors of the information theory society as well as the editorial boards of the Transactions on Information Theory and Foundations and Trends in Communications and Information Theory. He is founding Director of the Stanford Compression Forum.
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Gordon Wetzstein
Associate Professor of Electrical Engineering and, by courtesy, of Computer Science
BioGordon Wetzstein is an Associate Professor of Electrical Engineering and, by courtesy, of Computer Science at Stanford University. He is the leader of the Stanford Computational Imaging Lab and a faculty co-director of the Stanford Center for Image Systems Engineering. At the intersection of computer graphics and vision, artificial intelligence, computational optics, and applied vision science, Prof. Wetzstein's research has a wide range of applications in next-generation imaging, wearable computing, and neural rendering systems. Prof. Wetzstein is a Fellow of Optica and the recipient of numerous awards, including an NSF CAREER Award, an Alfred P. Sloan Fellowship, an ACM SIGGRAPH Significant New Researcher Award, a Presidential Early Career Award for Scientists and Engineers (PECASE), an SPIE Early Career Achievement Award, an Electronic Imaging Scientist of the Year Award, an Alain Fournier Ph.D. Dissertation Award as well as many Best Paper and Demo Awards.
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Eric Wheeler
Systems and Web Developer, Electrical Engineering
Web Dvlpr 3, Electrical EngineeringCurrent Role at StanfordSystems and Web Developer, Electrical Engineering
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Jennifer Widom
Frederick Emmons Terman Dean of the School of Engineering, Fletcher Jones Professor of Computer Science and Professor of Electrical Engineering
BioJennifer Widom is the Frederick Emmons Terman Dean of the School of Engineering and the Fletcher Jones Professor in Computer Science and Electrical Engineering at Stanford University. She served as Computer Science Department Chair from 2009-2014 and School of Engineering Senior Associate Dean from 2014-2016. Jennifer received her Bachelor's degree from the Indiana University Jacobs School of Music in 1982 and her Computer Science Ph.D. from Cornell University in 1987. She was a Research Staff Member at the IBM Almaden Research Center before joining the Stanford faculty in 1993. Her research interests span many aspects of nontraditional data management. She is an ACM Fellow and a member of the National Academy of Engineering and the American Academy of Arts & Sciences; she received a Guggenheim Fellowship in 2000, the ACM SIGMOD Edgar F. Codd Innovations Award in 2007, the ACM-W Athena Lecturer Award in 2015, and the EPFL-WISH Foundation Erna Hamburger Prize in 2018.
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Keith Winstein
Associate Professor of Computer Science and, by courtesy, of Electrical Engineering
BioKeith Winstein is an associate professor of computer science and, by courtesy, of electrical engineering at Stanford University. His research group creates new kinds of networked systems by rethinking abstractions around communication, compression, and computing. Some of his group’s research has found broader use, including the Mosh tool, the Puffer video-streaming site, the Lepton compression tool, the Mahimahi network emulators, and the gg lambda-computing framework. He has received the SIGCOMM Rising Star Award, the Sloan Research Fellowship, the NSF CAREER Award, the Usenix NSDI Community Award (2020, 2017), the Usenix ATC Best Paper Award, the Applied Networking Research Prize, the SIGCOMM Doctoral Dissertation Award, and a Sprowls award for best doctoral thesis in computer science at MIT. Winstein previously served as a staff reporter at The Wall Street Journal and worked at Ksplice, a startup company (now part of Oracle) where he was the vice president of product management and business development and also cleaned the bathroom. He did his undergraduate and graduate work at MIT.
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Robin Linus
Ph.D. Student in Electrical Engineering, admitted Autumn 2024
BioCypherpunk | Bitcoin researcher | Creator of BitVM
Focusing on the scalability, privacy, and usability of Bitcoin.
https://robinlinus.com -
Christopher Wolters
Affiliate, Program-Mitra, S.
BioChristopher Wolters is an M.Sc. candidate in Electrical and Computer Engineering at the Technical University of Munich (TUM). His research focuses on artificial intelligence, bio-inspired computing, and hardware-software co-design. He is currently a Visiting Student Researcher at Stanford University, where he works on AI computing architectures under the supervision of Prof. Subhasish Mitra and Prof. Ulf Schlichtmann.
Christopher has conducted research at the University of Tokyo on compute-in-memory architectures and at Duke University on neuromorphic hardware, and he completed academic training at ETH Zurich in Electrical and Computer Engineering. His accolades include the Max Weber Program scholarship by the German state, the Best Poster Award at MWSCAS 2023, and the NSF-CISE MWSCAS Student Award. -
H.-S. Philip Wong
Willard R. and Inez Kerr Bell Professor in the School of Engineering
BioH.-S. Philip Wong is the Willard R. and Inez Kerr Bell Professor in the School of Engineering at Stanford University. He joined Stanford University as Professor of Electrical Engineering in 2004. From 1988 to 2004, he was with the IBM T.J. Watson Research Center. From 2018 to 2020, he was on leave from Stanford and was the Vice President of Corporate Research at TSMC, the largest semiconductor foundry in the world, and since 2020 remains the Chief Scientist of TSMC in a consulting, advisory role.
He is a Fellow of the IEEE and received the IEEE Andrew S. Grove Award, the IEEE Technical Field Award to honor individuals for outstanding contributions to solid-state devices and technology, as well as the IEEE Electron Devices Society J.J. Ebers Award, the society’s highest honor to recognize outstanding technical contributions to the field of electron devices that have made a lasting impact.
He is the founding Faculty Co-Director of the Stanford SystemX Alliance – an industrial affiliate program focused on building systems and the faculty director of the Stanford Nanofabrication Facility – a shared facility for device fabrication on the Stanford campus that serves academic, industrial, and governmental researchers across the U.S. and around the globe, sponsored in part by the National Science Foundation. He is the Principal Investigator of the Microelectronics Commons California-Pacific-Northwest AI Hardware Hub, a consortium of over 40 companies and academic institutions funded by the CHIPS Act. He is a member of the US Department of Commerce Industrial Advisory Committee on microelectronics. -
S Simon Wong
Professor of Electrical Engineering, Emeritus
BioWong studies the fabrication and design of high-performance integrated circuits.
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Bruce A. Wooley
The Robert L. and Audrey S. Hancock Professor in the School of Engineering, Emeritus
BioBruce Wooley is the Robert L. and Audrey S. Hancock Professor of Engineering, Emeritus, in the Department of Electrical Engineering at Stanford University. He received a Ph.D. degree in Electrical Engineering from the University of California, Berkeley in 1970, and from 1970 to 1984 he was a member of the research staff at Bell Laboratories in Holmdel, NJ. He joined the faculty at Stanford in 1984. At Stanford he has served as the Chair of the Department of Electrical Engineering, the Senior Associate Dean of Engineering and the Director of the Integrated Circuits Laboratory. His research is in the field of integrated circuit design, where his interests include low-power mixed-signal circuit design, oversampling analog-to-digital and digital-to-analog conversion, circuit design techniques for video and image data acquisition, high-speed embedded memory, high-performance packaging and testing, and circuits for wireless and wireline communications.
Prof. Wooley is a Fellow of the IEEE and a past President of the IEEE Solid-State Circuits Society. He has served as the Editor of the IEEE Journal of Solid-State Circuits and as the Chairman of both the International Solid-State Circuits Conference (ISSCC) and the Symposium on VLSI Circuits. Awards he has received include the University Medal from the University of California, Berkeley, the IEEE Journal of Solid-State Circuits Best Paper Award, the Outstanding Alumnus Award from the EECS Department at the University of California, Berkeley, and the IEEE Donald O. Pederson Award in Solid-State Circuits. -
Lei Xing
Jacob Haimson and Sarah S. Donaldson Professor and Professor, by courtesy, of Electrical Engineering
Current Research and Scholarly Interestsartificial intelligence in medicine, medical imaging, Image-guided intervention, molecular imaging, biology guided radiation therapy (BGRT), treatment plan optimization
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Kuang Xu
Associate Professor of Operations, Information and Technology at the Graduate School of Business and, by courtesy, of Electrical Engineering
BioKuang Xu is an Associate Professor of Operations, Information and Technology at Stanford Graduate School of Business, and Associate Professor by courtesy with the Electrical Engineering Department, Stanford University. Born in Suzhou, China, he received the B.S. degree in Electrical Engineering (2009) from the University of Illinois at Urbana-Champaign, and the Ph.D. degree in Electrical Engineering and Computer Science (2014) from the Massachusetts Institute of Technology.
His research primarily focuses on understanding fundamental properties and design principles of large-scale stochastic systems using tools from probability theory and optimization, with applications in queueing networks, healthcare, privacy and machine learning. He received First Place in the INFORMS George E. Nicholson Student Paper Competition (2011), the Best Paper Award, as well as the Kenneth C. Sevcik Outstanding Student Paper Award at ACM SIGMETRICS (2013), and the ACM SIGMETRICS Rising Star Research Award (2020). He currently serves as an Associate Editor for Operations Research and Management Science. -
Sheng Xu
Professor of Anesthesiology, Perioperative & Pain Medicine (Department Research) and, by courtesy, of Electrical Engineering
BioDr. Sheng Xu is a tenured professor and the inaugural Director of Emerging Technologies in the Department of Anesthesiology, Perioperative and Pain Medicine at Stanford University, with a courtesy appointment in Electrical Engineering. He earned his B.S. degree in Chemistry from Peking University and his Ph.D. in Materials Science and Engineering from the Georgia Institute of Technology. Subsequently, he pursued postdoctoral studies at the Materials Research Laboratory at the University of Illinois at Urbana-Champaign. He then spent 10 years on the faculty at UC San Diego before joining Stanford in 2025. His research group is interested in developing new materials and fabrication methods for soft electronics. His research has been presented to the United States Congress as a testimony to the importance and impact of NIH funding.
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Yoshihisa Yamamoto
Professor of Electrical Engineering and of Applied Physics, Emeritus
Current Research and Scholarly InterestsExperimental Quantum Optics, Semiconductor Physics, Quantum Information
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Jerry Yang
Ph.D. Student in Electrical Engineering, admitted Autumn 2020
BioJerry A. Yang is a PhD student in electrical engineering at Stanford University. He received his BS in electrical engineering from the University of Texas at Austin and MA in Education from Stanford University. He currently works on strain engineering in two-dimensional materials in Prof. Eric Pop's lab. In addition, he works on equity issues in engineering education in Prof. Sheri Sheppard's Designing Education Lab. His research interests span novel materials, devices, and systems for next-generation computing, engineering education research methods, and critical theories in engineering education. He is a student member of the Institute for Electrical and Electronics Engineers (IEEE), Materials Research Society (MRS), and American Society of Engineering Education (ASEE).
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Bill Yen
Ph.D. Student in Electrical Engineering, admitted Autumn 2023
BioBill Yen is a Ph.D. candidate in the Department of Electrical Engineering at Stanford University working in the area of low-power Internet of Things (IoT) systems. He is an interdisciplinary maker and environmental scientist passionate about solving issues related to food, water, and energy using smart technologies.
Yen's experience in industry (General Motors, CNH Industrial) and academic research (Northwestern - soil-powered computing, Stanford - low-power wireless communication) cultivated his interest in designing self-powered computing devices that boost system efficiency while lowering the environmental impact of existing processes. His work has been featured by The Independent, Fast Company, MIT Technology Review China, Hackster.io, and more. He is also a recipient of the Stanford Graduate Fellowship in Science & Engineering. -
Serena Yeung-Levy
Assistant Professor of Biomedical Data Science and, by courtesy, of Electrical Engineering and of Computer Science
BioDr. Serena Yeung-Levy is an Assistant Professor of Biomedical Data Science and, by courtesy, of Computer Science and of Electrical Engineering at Stanford University. Her research focus is on developing artificial intelligence and machine learning algorithms to enable new capabilities in biomedicine and healthcare. She has extensive expertise in deep learning and computer vision, and has developed computer vision algorithms for analyzing diverse types of visual data ranging from video capture of human behavior, to medical images and cell microscopy images.
Dr. Yeung-Levy leads the Medical AI and Computer Vision Lab at Stanford. She is affiliated with the Stanford Artificial Intelligence Laboratory, the Clinical Excellence Research Center, and the Center for Artificial Intelligence in Medicine & Imaging. She is also a Chan Zuckerberg Biohub Investigator and has served on the NIH Advisory Committee to the Director Working Group on Artificial Intelligence. -
Jeffrey Yu
Ph.D. Student in Electrical Engineering, admitted Autumn 2023
BioI am a first year EE Ph.D. student majoring at Stanford University. I received my M.S. degree in Electrical Engineering from Stanford University in 2023 and my B.S. degree in Computer Engineering from UC San Diego in 2021. I am interested in DNN quantization and digital accelerator design.
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Sajung Yun, PhD, MBA
Visiting Scholar, Center for East Asian Studies
Affiliate, US-Asia Technology Management CenterBioDr. Sajung Yun is a multifaceted scholar and entrepreneur whose work bridges the disciplines of genomics, biomedical sciences, and artificial intelligence. At Stanford, his current research focuses on AI's self-recognition, self-protection, and self-perpetuation mechanisms and their implications in relation to Artificial General Intelligence and Super-Specialized Generalist Intelligence in medicine. He also serves as Adjunct Professor of Bioinformatics at Johns Hopkins University where he teaches bioinformatics courses over the last ten years.
Dr. Yun earned his Ph.D. in Biomedical Sciences from the John A. Burns School of Medicine and his MBA with concentrations in Healthcare Management and Entrepreneurship from Johns Hopkins University, blending rigorous scientific training with strategic leadership in medical innovation. He also attended M.D. program and completed 121 credits at John A. Burns School of Medicine. His academic appointments also include a concurrent role as Adjunct Professor in Biomedical Engineering at Ulsan National Institute of Science and Technology (UNIST), where he continues to contribute to global collaborations in AI-driven bioinformatics and healthcare system optimization.
As the Founder and CEO of Predictive AI, Dr. Yun leads a digital health company specializing in AI-based personalized preventive medicine platforms. Under his leadership, the company has been recognized for excellence in innovation, receiving distinctions such as the 2023 and 2022 4th Industrial Revolution Awards in AI and Biohealth, and the 2024 Venture Business Association President’s Award at the 6th Korea SME & Startup Awards. In recognition of his contributions to global innovation and leadership, Dr. Yun was named a 2025 Forbes Global CEO Delegate. In 2026, he lead his company to win Honoree Award in CES.
Dr. Yun’s professional career began as a Research Fellow at the U.S. National Institutes of Health (NIH), where he investigated advanced gene editing and genetic surgical methods. His research portfolio spans topics including next-generation sequencing data analysis, MRI volumetric analysis, and AI applications in biomedical imaging. His numerous publications and work continues to contribute to the evolving landscape of digital healthcare, emphasizing the convergence of data science, clinical insight, and artificial intelligence for human health advancement. -
Howard Zebker
Kwoh Ting Li Professor in the School of Engineering and Professor of Geophysics
Current Research and Scholarly InterestsResearch
My students and I study the surfaces of Earth and planets using radar remote sensing methods. Our specialization is interferometric radar, or InSAR. InSAR is a technique to measure mm-scale surface deformation at fine resolution over wide areas, and much of our work follows from applying this technique to the study of earthquakes, volcanoes, and human-induced subsidence. We also address global environmental problems by tracking the movement of ice in the polar regions. whose ice mass balance affects sea level rise and global climate. We participate in NASA space missions such as Cassini, in which we now are examining the largest moon of Saturn, Titan, to try and deduce its composition and evolution. Our work includes experimental observation and modeling the measurements to best understand processes affecting the Earth and solar system. We use data acquired by spaceborne satellites and by large, ground-based radar telescopes to support our research.
Teaching
I teach courses related to remote sensing methods and applications, and how these methods can be used to study the world around us. At the undergraduate level, these include introductory remote sensing uses of the full electromagnetic spectrum to characterize Earth and planetary surfaces and atmospheres, and methods of digital image processing. I also teach a freshman and sophomore seminar course on natural hazards. At the graduate level, the courses are more specialized, including the math and physics of two-dimensional imaging systems, plus detailed ourses on imaging radar systems for geophysical applications.
Professional Activities
InSAR Review Board, NASA Jet Propulsion Laboratory (2006-present); editorial board, IEEE Proceedings (2005-present); NRC Earth Science and Applications from Space Panel on Solid Earth Hazards, Resources, and Dynamics (2005-present); Chair, Western North America InSAR (WInSAR) Consortium (2004-06); organizing committee, NASA/NSF/USGS InSAR working group; International Union of Radioscience (URSI) Board of Experts for Medal Evaluations (2004-05); National Astronomy and Ionospheric Center, Arecibo Observatory, Visiting Committee, (2002-04; chair, 2003-04); NASA Alaska SAR Facility users working group (2000-present); associate editor, IEEE Transactions on Geoscience and Remote Sensing (1998-present); fellow, IEEE (1998) -
Rachel (Yinghao) Zhang
Managing Director of Industry Partnerships, Stanford SystemX Alliance, Electrical Engineering
BioRachel is the Managing Director of Industry Partnerships at SystemX.
As an innovative business leader, Rachel has launched and expanded businesses across the U.S., Asia, and global markets for tech companies including Alibaba, Ant Group, and Microchip.
During her tenure as Senior Advisor at Ant Group, she also incubated a philanthropic initiative to cultivate 10,000 technology leaders over a decade, aiming to bridge the digital divide and drive economic growth in emerging markets.
Rachel is passionate about harnessing technology for good, driving innovation, and bridging industry collaboration to create a broader meaningful impact.
Rachel is a Stanford GSB alumna. -
Zhe Zhang
Postdoctoral Scholar, Electrical Engineering
BioEPFL Ph.D. in Photonics 2024
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Orr Zohar
Ph.D. Student in Electrical Engineering, admitted Autumn 2021
Masters Student in Computer Science, admitted Autumn 2023BioOrr Zohar is a PhD candidate in Electrical Engineering at Stanford University and a Knight-Hennessy Scholar. He builds large-scale multimodal foundation models - spanning data curation, pretraining, and post-training - with a focus on video understanding, long-horizon reasoning, and robust transfer under real-world distribution shift. His work includes open-source model and dataset efforts and methods for evaluation and alignment of multimodal systems, with an emphasis on turning research into deployment-ready learning systems.
Before Stanford, he earned a BSc in Chemical Engineering (summa cum laude) and an MSc in Electrical Engineering from the Technion–Israel Institute of Technology, and worked as a machine learning and algorithms engineer at proteanTecs. Earlier research experiences include applied sensing and medical-imaging work. -
James Zou
Associate Professor of Biomedical Data Science and, by courtesy, of Computer Science and of Electrical Engineering
Current Research and Scholarly InterestsMy group works on both foundations of statistical machine learning and applications in biomedicine and healthcare. We develop new technologies that make ML more accountable to humans, more reliable/robust and reveals core scientific insights.
We want our ML to be impactful and beneficial, and as such, we are deeply motivated by transformative applications in biotech and health. We collaborate with and advise many academic and industry groups.
