Assistant Professor Department of Quantitative Theory & Methods Department of Economics (by courtesy) Goizueta Business School (by courtesy) Emory University Address: 581 PAIS Building, 36 Eagle Row ruoxuan.xiong@emory.edu [Google Scholar] [CV]

I am an assistant professor of Quantitative Theory and Methods at Emory University since Fall 2021. My 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. I received my Ph.D. in Management Science and Engineering from Stanford, advised by Markus Pelger. I was a postdoctoral fellow at the Stanford Graduate School of Business mentored by Susan Athey and Mohsen Bayati.

Research

Working Papers

• Data-Driven Switchback Experiments: Theoretical Tradeoffs and Empirical Bayes Designs
  with Alex Chin and Sean Taylor
  Preliminary version: Bias-Variance Tradeoffs for Designing Simultaneous Temporal Experiments
  KDD Workshop on Causal Discovery, Prediction and Decision, 2023
  

• Efficient Treatment Effect Estimation in Observational Studies under Heterogeneous Partial Interference [slides] [talk] [code]
  with Zhaonan Qu, Jizhou Liu, and Guido Imbens
  

Recent Publications

• Optimal Experimental Design for Staggered Rollouts [slides] [code]
  with Susan Athey, Mohsen Bayati, and Guido Imbens
  Management Science, accepted
  2020 MSOM Student Paper Competition Finalist

• Target PCA: Transfer Learning Large Dimensional Panel Data [slides]
  Internet Appendix
  with Junting Duan and Markus Pelger
  Journal of Econometrics, accepted
  

• Federated Causal Inference in Heterogeneous Observational Data [slides] [code] [lay abstract]
  with Allison Koenecke, Michael Powell, Zhu Shen, Joshua T. Vogelstein, and Susan Athey
  Statistics in Medicine, 2023, 1–22 doi: 10.1002/sim.9868
  

• Large Dimensional Latent Factor Modeling with Missing Observations and Applications to Causal Inference [slides]
  Internet Appendix
  with Markus Pelger
  Journal of Econometrics, 2023, 233(1), 271-301
  2019 George Nicholson Student Paper Competition Honorable Mention

• Interpretable Sparse Proximate Factors for Large Dimensions [slides]
  with Markus Pelger
  Journal of Business & Economic Statistics, 2022, 40(4), 1642-1664
  

• State-Varying Factor Models of Large Dimensions [slides]
  Internet Appendix
  with Markus Pelger
  Journal of Business & Economic Statistics, 2022, 40(3), 1315-1333
  

• Stable Prediction with Model Misspecification and Agnostic Distribution Shift
  with Kun Kuang, Peng Cui, Susan Athey, and Bo Li
  AAAI 2020
  

• Stable Predictions across Unknown Environments
  with Kun Kuang, Peng Cui, Susan Athey, and Bo Li
  KDD 2018 (oral)
  

Idle Manuscripts

• Deep Learning Stock Volatility with Google Domestic Trends
  with Eric P. Nichols and Yuan Shen
  

Teaching

• Machine Learning: Fall 2023

• Machine Learning and Causal Inference: Fall 2021, Spring 2022, Fall 2022

• Quantitative Finance: Fall 2022, Spring 2023, Fall 2023

Education

• 2021: postdoc at Stanford Graduate School of Business (mentors: Susan Athey and Mohsen Bayati)

• 2020: Ph.D. in Management Science and Engineering at Stanford University (advisor: Markus Pelger)

• 2014: B.S. from Peking University