School of Engineering
Showing 641-660 of 680 Results
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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. -
Jiajun Wu
Assistant Professor of Computer Science and, by courtesy, of Psychology
BioJiajun Wu is an Assistant Professor of Computer Science and, by courtesy, of Psychology at Stanford University, working on computer vision, machine learning, robotics, and computational cognitive science. Before joining Stanford, he was a Visiting Faculty Researcher at Google Research. He received his PhD in Electrical Engineering and Computer Science from the Massachusetts Institute of Technology. Wu's research has been recognized through the Young Investigator Programs (YIP) by ONR and by AFOSR, the NSF CAREER award, the Okawa research grant, the AI's 10 to Watch by IEEE Intelligent Systems, paper awards and finalists at ICCV, CVPR, SIGGRAPH Asia, ICRA, CoRL, and IROS, dissertation awards from ACM, AAAI, and MIT, the 2020 Samsung AI Researcher of the Year, and faculty research awards from Microsoft, Google, Nvidia, J.P. Morgan, Samsung, Amazon, and Meta.
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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. -
Renyuan Xu
Assistant Professor of Management Science and Engineering
BioRenyuan Xu is an assistant professor of Management Science and Engineering (MS&E) at Stanford University. Prior to joining Stanford, she held positions at New York University (2024-2025) and the University of Southern California (2021–2024), and was a Hooke Research Fellow at the Mathematical Institute, University of Oxford (2019–2021). She received her Ph.D. in Operations Research from the University of California, Berkeley in 2019. Renyuan's current research interests include mathematical finance, stochastic analysis, stochastic controls and games, and machine learning theory. She received an NSF CAREER Award in 2024, the SIAM Activity Group on Financial Mathematics and Engineering Early Career Prize in 2023, and two JP Morgan AI Faculty Research Awards in 2022 and 2025.
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Sheng Xu
Professor of Anesthesiology, Perioperative & Pain Medicine (Department Research) and, by courtesy, of Electrical Engineering and of Materials Science & 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 courtesy appointments in Electrical Engineering and Materials Science and 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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Daniel Yamins
Associate Professor of Psychology and of Computer Science
Current Research and Scholarly InterestsOur lab's research lies at intersection of neuroscience, artificial intelligence, psychology and large-scale data analysis. It is founded on two mutually reinforcing hypotheses:
H1. By studying how the brain solves computational challenges, we can learn to build better artificial intelligence algorithms.
H2. Through improving artificial intelligence algorithms, we'll discover better models of how the brain works.
We investigate these hypotheses using techniques from computational modeling and artificial intelligence, high-throughput neurophysiology, functional brain imaging, behavioral psychophysics, and large-scale data analysis. -
Haoxue Yan
Lecturer
BioHaoxue ("How-sh-ew-eh", she/her) is a Lecturer in the Department of Materials Science and Engineering (MSE). Though Haoxue is trained in metallurgy in her graduate studies, she constantly seeks to expand her knowledge base so that she can make materials science interesting, relevant, and approachable for her students. In her classroom, Haoxue is committed to fostering an inclusive and engaging environment that promotes a sense of curiosity and life-long learning in her students as they grow into observant and critical thinkers.
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Diyi Yang
Assistant Professor of Computer Science
BioDiyi Yang is an Assistant Professor in Computer Science at Stanford University. Professor Yang's research interests are Computational Social Science and Natural Language Processing. Her research goal is to understand the social aspects of language and then build socially aware NLP systems to better support human-human and human-computer interaction. Professor Yang received her PhD from the School of Computer Science, Carnegie Mellon University, and her bachelor's degree from Shanghai Jiao Tong University, China. Her work has received multiple best paper nominations or awards at ICWSM, EMNLP, SIGCHI, ACL, and CSCW. She is a recipient of Forbes 30 under 30 in Science, IEEE “AI 10 to Watch”, the Intel Rising Star Faculty Award, Microsoft Research Faculty Fellowship, and NSF CAREER Award.
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Fan Yang
Associate Professor of Orthopaedic Surgery and of Bioengineering
Current Research and Scholarly InterestsOur lab’s mission is to develop therapies for regenerating human tissues lost due to diseases or aging, and to build tissue engineered 3D models for understanding disease progression and informing drug discovery. We invent biomaterials and engineering tools to elucidate and modulate biology, and also use biology to inform materials and engineering design. Our work is highly interdisciplinary, and is driven by unmet clinical needs or key gaps in biology.
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Yunzhi Peter Yang
Professor of Orthopaedic Surgery and, by courtesy, of Materials Science and Engineering and of Bioengineering
On Partial Leave from 12/01/2025 To 05/31/2026Current Research and Scholarly InterestsThe Yang Lab focuses on next-generation solutions at the intersection of 3D printing, regenerative medicine, modular tissue engineering, biomaterials, and medical device innovation. Our research focuses on engineering dynamic, biomimetic microenvironments that promote cell growth, tissue regeneration, and functional restoration. We develop transformative technologies to treat a broad spectrum of musculoskeletal conditions—including multi-tissue healing challenges and complex traumatic injuries.
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Yinyu Ye
Kwoh-Ting Li Professor in the School of Engineering, Emeritus
Current Research and Scholarly InterestsMy current research interests include Continuous and Discrete Optimization, Algorithm Development and Analyses, Algorithmic Game/Market Theory and Mechanism-Design, Markov Decision Process and Reinforcement Learning, Dynamic/Online Optimization and Resource Allocation, and Stochastic and Robust Decision Making. These areas have been the unique and core disciplines of MS&E, and extended to new application areas in AI, Machine Learning, Data Science, and Business Analytics.
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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.
