School of Engineering


Showing 651-660 of 689 Results

  • Bruce A. Wooley

    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

    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 Google, J.P. Morgan, Samsung, Amazon, and Meta.

  • Lei Xing

    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

  • Kuang Xu

    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

    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.

  • Sheng Xu

    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.