Xi Chen

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NYU Stern School of Business
TOPS Department


I am currently an Associate 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 School of Computer Science at Carnegie Mellon University. My doctoral dissertation was directed by the committee members: Dr. Jaime Carbonell, Dr. Tom Mitchell, Dr. Larry Wasserman, and Dr. Robert Tibshirani (from Stanford). Before that, I obtained my master of science in Industry Administration (Operations Research) from the ACO (algorithms, combinatorics and optimization) program in the Tepper School of Business at Carnegie Mellon. My master's work is advised by Prof. Manuel Blum.

Research Interests

  • Statistical Machine Learning: Statistical inference for Online Streaming Data, Large-scale Distributed Data, and High-dimensional Data.

  • Online Learning and Decision-making: Multi-armed Bandit and Reinforcement Learning, Stochastic Optimization and Distributionally Robust Optimization.

  • Online Learning and Trustworthy Learning for Operations & E-commerce: Dynamic Pricing, Assortment Optimization for Recommendation, Digital Advertising, Privacy and Fairness

  • Blockchain and Web3 (recently): Mechanism Design in Blockchain, Security, and AMM/DeFI

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