Xi Chen

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NYU Stern School of Business
TOPS Department


I am currently a Professor and Andre Meyer Faculty Fellow at the Department of Technology, Operations, and Statistics at Stern School of Business at New York University. I also hold affiliated faculty positions at Courant Institute of Mathematical Sciences and Center for Data Science.

Before joining NYU Stern, I did a postdoc with Professor Michael I. Jordan at the University of California, Berkeley. I earned my doctoral degree from Carnegie Mellon University. Before that, I obtained my master of science in Industry Administration (Operations Research) from the ACO program in the Tepper School of Business at Carnegie Mellon.

Research Interests

  • Statistical Inference and Optimization: Statistical inference for Online Streaming Data, Large-scale Distributed Data, and High-dimensional Data, Stochastic Optimization and Distributionally Robust Optimization.

  • Online Learning and Trustworthy Learning for Operations & E-commerce: Multi-armed Bandit, Dynamic Pricing, Assortment Optimization for Recommender System, Digital Advertising

  • Blockchain, Web3, and Quant Research: Mechanism Design in Blockchain, Decentralized Finance, and Quantitative Finance

Recent News

  1. 12/2022 My paper Bayesian-Nash-Incentive-Compatible Mechanism for Blockchain Transaction Fee Allocation won the Best Paper Award at NeurIPS Workshop on Decentralization and Trustworthy Machine Learning in Web3.

  2. 09/2022, My book The Elements of Joint Learning and Optimization in Operations Management co-edited with Stefanus Jasin and Cong Shi have been published in Springer Series in Supply Chain Management.

  3. 08/2022, My papers Delta Hedging Liquidity Positions on Automated Market Makers and Bayesian-Nash-Incentive-Compatible Mechanism for Blockchain Transaction Fee Allocation were accepted by Crypto Economics Security Conference at UC Berkeley.

  4. 06/2022, I am honored to be appointed as Andre Meyer Faculty Fellow by NYU Stern School of Business.

  5. 05/2022, My paper Active Learning for Contextual Search with Binary Feedbacks co-authored with Quanquan Liu and Yining Wang has been accepted by Management Science.

  6. 01/2022, I am elected to COPSS Leadership Academy.

  7. 01/2022, My paper Robust Dynamic Pricing with Demand Learning in the Presence of Outlier Customers co-authored with Yining Wang is accepted by Operations Research.

  8. 01/2022, My paper Predicting Future Earnings Changes Using Machine Learning and Detailed Financial Data co-authored with Yang Ha (Tony) Cho, Yiwei Dou, and Baruch Lev is accepted by Journal of Accounting Research.

  9. 11/2021, I am appointed as an AE of the Annals of Statistics.

  10. 06/2021, I become an Elected Member of the International Statistical Institute (ISI).

  11. 06/2021, My paper Privacy-Preserving Dynamic Personalized Pricing with Demand Learning co-authored with David Simchi-Levi and Yining Wang is accepted by Management Science.

  12. 05/2021, I am recognized by Poets & Quants as The World's Best 40 Under 40 MBA Professors.

  13. 05/2021, My paper Online Covariance Matrices Estimation of Stochastic Gradient Descent co-authored with Wanrong Zhu and Wei Biao Wu is accepted by the Journal of the American Statistical Association (Theory and Methods).

Selected Awards

  • Andre Meyer Faculty Fellow, 2022

  • COPSS Leadership Academy, 2022

  • Poets & Quants: The World's Best 40 Under 40 MBA Professors, 2021

  • Elected Member of the International Statistical Institute (ISI), 2021

  • ICSA Outstanding Young Researcher Award, 2019

  • Honorable Mention in INFORMS Junior Faculty Interest Group Paper Award (JFIG), 2019

  • Forbes 30 Under 30 in Science, 2017

Editorial Appointments

  • Associate Editor: Management Science

  • Associate Editor: Operations Research

  • Associate Editor: Management Science: (Special Issue on Data-Driven Prescriptive Analytics)