Xi Chen

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Email:

xc13(AT)stern(DOT)nyu(DOT)edu

Address:

NYU Stern School of Business
IOMS Department
44 West 4-th St., Office 8-50
New York, NY, 10012

Biography

I am currently an Associate Professor 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.

Selected Awards

  • National Science Foundation Faculty Early Career Development (CAREER) Award, 2019

  • Forbes 30 Under 30 in Science

  • Facebook Faculty Research Award, 2020

  • JPMorgan Chase Faculty Research Award, 2020

  • ICSA Outstanding Young Researcher Award, 2019

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

  • Bloomberg Data Science Research Grant, 2018

  • Adobe Data Science Research Award, 2017

  • Google Faculty Research Award, 2015

Research Interests

  • Statistical Inference and Learning: Statistical inference for Online Streaming Data (based on Stochastic Optimization), Distributed Data, and High-dimensional Data.

  • Nonparametric Estimation and Shape-restricted Nonparametric Inference

  • Multi-armed Bandit and Online Decision-making with Applications to Rank Aggregation, Crowdsourcing, and Revenue Management (Dynamic Pricing and Assortment Planning)

  • Optimization: Stochastic Optimization, Robust Optimization, and Discrete Optimization with Applications to Operations Management

Some representative papers

  1. Statistical Inference for Model Parameters in Stochastic Gradient Descent
    Xi Chen, Jason D. Lee, Xin T. Tong, and Yichen Zhang.
    Annals of Statistics, 48(1): 251–273, 2020. [video]

  2. Quantile Regression Under Memory Constraint
    Xi Chen, Weidong Liu, and Yichen Zhang.
    Annals of Statistics, 47(6): 3244–3273, 2019. [Code]

  3. Testing Independence with High-dimensional Correlated Samples
    Xi Chen and Weidong Liu.
    Annals of Statistics, 46(2): 866-894, 2018

  4. Robust Dynamic Assortment Optimization in the Presence of Outlier Customers
    Xi Chen, Akshay Krishnamurthy, and Yining Wang.

  5. Optimal Design of Process Flexibility for General Production Systems
    Xi Chen, Tengyu Ma, Jiawei Zhang, and Yuan Zhou.
    Operations Research, 67(2), 516–531, 2019

  6. Near-Optimal Policies for Dynamic Multinomial Logit Assortment Selection Models
    Yining Wang, Xi Chen, and Yuan Zhou.
    In Proceedings of Advances in Neural Information Processing Systems (NeurIPS), 2018.

Editorial Appointments