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Ruoxuan XiongAssistant Professor | Data & Decision Sciences
Biography
Ruoxuan received her Ph.D. in Management Science and Engineering from Stanford, advised by Markus Pelger. She was a postdoctoral fellow at the Stanford Graduate School of Business mentored by Susan Athey and Mohsen Bayati.
Education
- Ph.D., Management Science and Engineering, 2020
- B.S., Urban and Rural Planning & Mathematics (double major), Peking University, 2014
Research and Recent Articles
Ruoxuan's research interests lie at the intersection of econometrics and operations management, focusing on causal inference, experimental design and factor modeling, with applications in finance and healthcare.
Publications
- Optimal Experimental Design for Staggered Rollouts [slides] [code]with Susan Athey, Mohsen Bayati, and Guido ImbensManagement Science, accepted2020 MSOM Student Paper Competition Finalist
- Large Dimensional Latent Factor Modeling with Missing Observations and Applications to Causal Inference [slides]Internet Appendixwith Markus PelgerJournal of Econometrics, 2023, 233(1), 271-3012019 George Nicholson Student Paper Competition Honorable Mention
- Interpretable Sparse Proximate Factors for Large Dimensions [slides]with Markus PelgerJournal of Business & Economic Statistics, 2022, 40(4), 1642-1664
- State-Varying Factor Models of Large Dimensions [slides]Internet Appendixwith Markus PelgerJournal of Business & Economic Statistics, 2022, 40(3), 1315-1333
- Stable Prediction with Model Misspecification and Agnostic Distribution Shiftwith Kun Kuang, Peng Cui, Susan Athey, and Bo LiAAAI 2020
- Preventing cytokine storm syndrome in COVID-19 using alpha-1 adrenergic receptor antagonists
with Maximilian F Konig, Mike Powell, Verena Staedtke, Ren-Yuan Bai, David L Thomas, Nicole Fischer, Sakibul Huq, Adham M Khalafallah, Allison Koenecke, Brett Mensh, Nickolas Papadopoulos, Kenneth W Kinzler, Bert Vogelstein, Joshua T Vogelstein, Susan Athey, Shibin Zhou, Chetan Bettegowda
Journal of Clinical Investigation 2020
- A Tractable Ellipsoidal Approximation for Voltage Regulation Problems
with Pan Li, Baihong Jin, Dai Wang, Alberto Sangiovanni-Vincentelli and Baosen Zhang
American Control Conference (ACC) 2019
- Stable Predictions across Unknown Environmentswith Kun Kuang, Peng Cui, Susan Athey, and Bo LiKDD 2018 (oral)
Teaching
- DATASCI 347: Causal Inference & Machine Learning
- DATASCI 385: Quantitative Finance
