Stanford University
Showing 501-537 of 537 Results
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Chenghan Xie
Ph.D. Student in Management Science and Engineering, admitted Autumn 2024
Current Research and Scholarly InterestsOptimization, theory & practice. Energy-aware AI, nerual-network structure & data center management.
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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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Wenhao Yang
Postdoctoral Scholar, Management Science and Engineering
BioWenhao Yang is a postdoctoral researcher in the Department of Management Science and Engineering (MS&E) at Stanford University, advised by Professor Jose Blanchet. He received his Ph.D. in Data Science (Statistics) from Peking University in 2023 and his B.S. in Statistics from the School of Mathematical Sciences at Peking University in 2018.
Wenhao’s research interests lie at the intersection of probability, statistics, and machine learning, with applications in operations research, reinforcement learning, and deep learning. His work focuses on developing modern statistical theory for large-scale models and designing practical algorithms with rigorous theoretical guarantees. His research has contributed to publications in leading venues including Annals of Statistics, IEEE Transactions on Pattern Analysis and Machine Intelligence, ICML, NeurIPS, ICLR, AISTATS, with additional papers currently under revisions at Annals of Applied Probability.
For more details, please visit Wenhao’s personal website: https://web.stanford.edu/~yangwh/ -
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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Angelina You
Masters Student, Management Science and Engineering
BioAngelina is a MS student in Management Science & Engineering at Stanford University, specializing in technology and engineering management. She is passionate about leveraging technology and analytics to address societal issues and assist the underprivileged. She has four years of data science and product experience at Meta and two other high-growth tech startups but she is also interested in entrepreneurship. Outside of work, she serves as a project-client manager for Statistics Without Borders and co-leads a graduate student startup community at Stanford. An explorer at heart, Angelina has a wide range of interests, including dancing, boxing, cooking, traveling, and cuddling with her baby Yorkie, Yoyo.
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Tijana Zrnic
Assistant Professor of Statistics and of Management Science and Engineering
BioTijana Zrnic is an Assistant Professor at Stanford University, jointly appointed between Statistics, Management Science & Engineering, and, by courtesy, Computer Science. She works on foundational questions in machine learning, statistics, and data-driven decision-making. Example topics of interest include AI-assisted statistical inference and data collection, performative prediction, and studying selection bias.
