Xi Chen

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NYU Stern School of Business
TOPS Department


I am currently a Full 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.

In 2021–2023, I contributed two years as a principal scientist at Amazon Ads, where I spearheaded a science team to advance forecasting and delivery systems in digital advertising. I also collaborated with industry giants such as Google, Meta, Adobe, JP Morgan, and Bloomberg have addressed a range of technical and business challenges, and obtained outstanding faculty research awards from each.

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.

See a more detailed bio on my NYU Stern homepage.

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. 05/2024 My forthcoming book, Web3: Blockchain, the New Economy, and the Self-Sovereign Internet, co-authored with a Harvard Business professor, a Yale Computer Science professor, and professional experts, will be published by Cambridge University Press this fall.

  2. 05/2024 My research paper, Proof-of-Learning with Incentive Security, proposes an new method to verify AI computations. This approach serves as a Proof-of-Useful-Work alternative to replace hash computations in blockchain mining.

  3. 05/2024 I was elected as a Fellow of the Institute of Mathematical Statistics (IMS).

  4. 01/2024 I'm thrilled to announce the publication of the book I co-edited, Beyond AI: ChatGPT, Web3, and the Business Landscape of Tomorrow by the Springer publisher.

  5. 11/2023 I am honored to be appointed as the Area Editor of Operations Research for the Department of Machine Learning and Data Science.

  6. 08/2023 I am honored to be promoted as the Full Professor at NYU Stern School of Business.

  7. 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.

  8. 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.

  9. 06/2022, I am honored to be appointed as Andre Meyer Faculty Fellow by NYU Stern School of Business.

  10. 01/2022, I am elected to COPSS Leadership Academy.

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

  12. 06/2021, I become an Elected Member of the International Statistical Institute (ISI).

  13. 09/2017, I was listed on the Forbes 30 Under 30 in North America

Editorial Appointments