School of Engineering


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  • 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 a JP Morgan AI Faculty Research Award in 2022.

  • 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. 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.