Stanford University
Showing 11-20 of 21 Results
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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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Yiqing Xu
Associate Professor of Political Science
BioDr. Xu’s research focuses on political methodology (particularly causal inference) and comparative politics. He received his PhD in Political Science from the Massachusetts Institute of Technology in 2016, an MA in Economics from Peking University in 2010, and a BA in Economics from Fudan University in 2007.
His work has been published in leading journals, including American Political Science Review, American Journal of Political Science, The Journal of Politics, Political Analysis, Journal of the American Statistical Association, Journal of Economic Perspectives, and Nature Human Behaviour.
He has received numerous professional awards, including the John T. Williams Dissertation Prize (2014), Best Article Award from American Journal of Political Science (2016), Miller Prize (2018, 2020), Editors’ Choice Award from Political Analysis (2018, 2025), Best Statistical Software Award (2024, 2025), and Emerging Scholar Award from the Society for Political Methodology (2024).
Dr. Xu is affiliated with the Stanford Causal Science Center and the Stanford Center on China’s Economy and Institutions, as well as other research institutions.
