Renyuan Xu
Assistant Professor of Management Science and Engineering
Bio
Renyuan 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.
Honors & Awards
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Jagdeep and Roshni Singh Faculty Fellow, Stanford (2025-)
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JP Morgan AI Faculty Research Award, JP Morgan Chase (2025)
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NSF CAREER Award, National Science Foudnation (2024)
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SIAM Activity Group on Financial Mathematics and Engineering Early Career Prize, Society for Industrial and Applied Mathematics (SIAM) (2023)
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JP Morgan AI Faculty Research Award, JP Morgan Chase (2022)
Professional Education
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Ph.D., University of California, Berkeley, Operations Research (2019)
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B.S., University of Science and Technology of China, Applied Mathematics (2014)
https://orcid.org/0000-0003-4293-34502025-26 Courses
- Advanced Investment Science
MS&E 245B (Win) - Machine Learning for Algorithmic Trading
MS&E 242 (Spr) - Stochastic Systems and Learning Theory with Applications in Finance
MS&E 342 (Spr) -
Independent Studies (1)
- Directed Reading and Research
MS&E 408 (Aut, Win, Spr, Sum)
- Directed Reading and Research
Stanford Advisees
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Doctoral Dissertation Co-Advisor (AC)
Puheng Li -
Doctoral (Program)
Yinbin Han, Lutong Hao, Jingwei Ji, Chenghan Xie
All Publications
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Inference of Utilities and Time Preference in Sequential Decision-Making
APPLIED MATHEMATICS AND OPTIMIZATION
2025; 92 (3)
View details for DOI 10.1007/s00245-025-10318-7
View details for Web of Science ID 001598797300001
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TAIL-GAN: Learning to Simulate Tail Risk Scenarios
MANAGEMENT SCIENCE
2025
View details for DOI 10.1287/mnsc.2023.00936
View details for Web of Science ID 001547468700001
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POLICY GRADIENT CONVERGES TO THE GLOBALLY OPTIMAL POLICY FOR NEARLY LINEAR-QUADRATIC REGULATORS
SIAM JOURNAL ON CONTROL AND OPTIMIZATION
2025; 63 (4): 2936-2963
View details for DOI 10.1137/23M1560781
View details for Web of Science ID 001572996200006
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Model-Free Analysis of Dynamic Trading Strategies
SIAM JOURNAL ON FINANCIAL MATHEMATICS
2025; 16 (2): 643-666
View details for DOI 10.1137/23M1581881
View details for Web of Science ID 001502641300013
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Delay-Adaptive Learning in Generalized Linear Contextual Bandits
MATHEMATICS OF OPERATIONS RESEARCH
2023
View details for DOI 10.1287/moor.2023.1358
View details for Web of Science ID 000955959600001
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A General Framework for Learning Mean-Field Games
MATHEMATICS OF OPERATIONS RESEARCH
2022
View details for DOI 10.1287/moor.2022.1274
View details for Web of Science ID 000815006100001
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Learning Mean-Field Games
edited by Wallach, H., Larochelle, H., Beygelzimer, A., d'Alche-Buc, F., Fox, E., Garnett, R.
NEURAL INFORMATION PROCESSING SYSTEMS (NIPS). 2019
View details for Web of Science ID 000534424305002
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Learning in Generalized Linear Contextual Bandits with Stochastic Delays
edited by Wallach, H., Larochelle, H., Beygelzimer, A., d'Alche-Buc, F., Fox, E., Garnett, R.
NEURAL INFORMATION PROCESSING SYSTEMS (NIPS). 2019
View details for Web of Science ID 000534424305022