Yichen Zhang

Assistant Professor of Quantitative Methods
Mitchell E. Daniels, Jr. School of Business
Purdue University

Contact

• Phone: +1 (765)496-5023

• E-post: zhang@purdue.edu

• Address: 403 Mitch Daniels Blvd, West Lafayette, IN, 47907

Education

• Ph.D., Department of Technology, Operations, Statistics,
  Stern School of Business, New York University, 2020

• B.S. in Mathematics, B.A. in Economics, Peking University, 2015

Research Interest

• Statistical Inference for Online Streaming Data, Bandits, and Reinforcement Learning

• Distributed Learning, Multi-task Learning, Transfer Learning

• Frequency-domain Time Series Analysis and Applications in Supply Chains

• Nonsmooth Optimization with Statistical Models

I am looking for Ph.D. students and research associates with various academic backgrounds and interests in statistics, machine learning, and operations research. I am also happy to host remote or onsite visitors with interests. Please contact me via email.

Service

• Associate Editor, Journal of Computational and Graphical Statistics (2024-)

Publications

• Distributed Estimation and Inference for Semi-parametric Binary Response Models.
  Xi Chen, Wenbo Jing, Weidong Liu, and Yichen Zhang.
  The Annals of Statistics, to appear, 2024+, [arXiv].
  

• Online Statistical Inference for Stochastic Optimization via Kiefer-Wolfowitz Methods.
  Xi Chen, Zehua Lai, He Li, and Yichen Zhang.
  Journal of the American Statistical Association, to appear, 2023+, [arXiv].
  

• Variance Reduction on General Adaptive Stochastic Mirror Descent.
  Wenjie Li, Zhanyu Wang, Yichen Zhang, and Guang Cheng.
  Machine Learning, 2022, 111, 4639-4677, [arXiv].

• First-order Newton-type Estimator for Distributed Estimation and Inference.
  Xi Chen, Weidong Liu, and Yichen Zhang.
  Journal of the American Statistical Association, 2022, 117(540), 1858-1874, [arXiv].

• Estimation of alpha, beta and Portfolio Weights in a Pure-Jump Model with Long Memory in Volatility.
  Yichen Zhang and Clifford M. Hurvich.
  Stochastic Processes and their Applications, 2022, 150, 972-994.

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

• Quantile Regression Under Memory Constraint.
  Xi Chen, Weidong Liu, and Yichen Zhang.
  The Annals of Statistics, 2019, 47(6), 3244-3273, [arXiv], [Code].

Preprints

• Information Design and Sharing in Supply Chains.
  Rene Caldentey, Avi Giloni, Clifford Hurvich, and Yichen Zhang. [SSRN].
  

• Online Tensor Inference.
  Xin Wen, Will Wei Sun, and Yichen Zhang. [arXiv].
  

• The Impact of Profit Differentials on the Value of a Little Flexibility.
  Shixin Wang, Jiawei Zhang, and Yichen Zhang. [SSRN].
  

• Online Estimation and Inference for Robust Policy Evaluation in Reinforcement Learning.
  Weidong Liu, Jiyuan Tu, Yichen Zhang, and Xi Chen. [arXiv].
  

• Acceleration of Stochastic Gradient Descent with Momentum by Averaging.
  Kejie Tang, Weidong Liu, Yichen Zhang, and Xi Chen. [arXiv].
  

• Online Statistical Inference for Matrix Contextual Bandit.
  Qiyu Han, Will Wei Sun, and Yichen Zhang. [arXiv].
  

• Online Statistical Inference for Contextual Bandits via Stochastic Gradient Descent.
  Xi Chen, Zehua Lai, He Li, and Yichen Zhang. [arXiv].
  

• Adaptive Data Fusion for Multi-task Non-smooth Optimization.
  Henry Lam, Kaizheng Wang, Yuhang Wu, and Yichen Zhang. [arXiv].