Wenxin (Steve) Zhou

Department of Mathematics
University of California, San Diego
9500 Gilman Dr.
La Jolla, CA 92093

Phone: 858-534-2640
E-mail: wez243@ucsd.edu
Office: AP&M 6131

I am an Associate Professor in the Statistics group within the Department of Mathematics at the University of California, San Diego. In August 2023, I will be joining the Department of Information and Decision Sciences in the College of Business Administration, University of Illinois at Chicago as an Associate Professor [Google Scholar & CV].

My recent research interests center around the development and analysis of statistical methods (estimation and inference) and optimization tools for structured high-dimensional data problems, including sparse regression, low-rank, and nonparametric models. The main focus is to develop robust and quantile-based methods in settings where the error distribution is heavy-tailed and/or heteroscedastic. I also work on developing and analyzing methods (from a statistical perspective) with nontraditional data types, such as distributed data, streaming/online data, multi-source data, and data subject to privacy concerns.

Complete Publications (arXiv)

Selected Publications

Smoothed quantile regression with large-scale inference
with Xuming He, Xiaoou Pan and Kean Ming Tan
Journal of Econometrics, 232(2): 367-388, 2023
[DOI] [R package] [Python code] [slides]

Please cite He et al. (2023)/Man et al. (2022) if you use conquer pacakge.

Scalable estimation and inference for censored quantile regression process
with Xuming He, Xiaoou Pan and Kean Ming Tan
The Annals of Statistics, 50(5): 2899-2924, 2022
[DOI] [supplement] [R code]

Communication-constrained distributed quantile regression with optimal statistical guarantees
with Kean Ming Tan and Heather Battey
Journal of Machine Learning Research, 23(272): 1-61, 2022

High-dimensional quantile regression: convolution smoothing and concave regularization
with Kean Ming Tan and Lan Wang
Journal of the Royal Statistical Society: Series B, 84(1): 205-233, 2022
[DOI] [supplement] [R package] [Python code]

Multiplier bootstrap for quantile regression: Non-asymptotic theory under random design
with Xiaoou Pan
Information and Inference: A Journal of the IMA, 10, 813-861, 2021
[DOI] [R code]

A new principle for tuning-free Huber regression
with Lili Wang, Chao Zheng and Wen Zhou
Statistica Sinica, 31, 2153-2177, 2021
[DOI] [supplement] [R package]

Iteratively reweighted l1-penalized robust regression
with Xiaoou Pan and Qiang Sun
Electronic Journal of Statistics, 15, 3287-3348, 2021
[DOI] [R package] [Python code]

Robust inference via multiplier bootstrap
with Xi Chen
The Annals of Statistics, 48, 1665-1691, 2020
[DOI] [supplement] [Matlab code]

Adaptive Huber regression
with Qiang Sun and Jianqing Fan
Journal of the American Statistical Association, 115, 254-265, 2020
[DOI] [arXiv] [R package] [slides]

FarmTest: Factor-adjusted robust multiple testing with approximate false discovery control
with Jianqing Fan, Yuan Ke and Qiang Sun
Journal of the American Statistical Association, 114, 1880-1893, 2019
[DOI] [R package]

User-friendly covariance estimation for heavy-tailed distributions
with Yuan Ke, Stanislav Minsker, Zhao Ren and Qiang Sun
Statistical Science, 34, 454-471, 2019

A new perspective on robust M-estimation: Finite sample theory and applications to dependence-adjusted multiple testing
with Koushiki Bose, Jianqing Fan and Han Liu
The Annals of Statistics, 46, 1904-1931, 2018
[DOI] [arXiv]

Are discoveries spurious? Distributions of maximum spurious correlations and their applications
with Jianqing Fan and Qi-Man Shao
The Annals of Statistics, 46, 989-1017, 2018
[DOI] [arXiv] [slides]

Max-norm optimization for robust matrix recovery
with Ethan X. Fang, Han Liu and Kim-Chuan Toh
Mathematical Programming, Series B, 167, 5-35, 2018
[DOI] [arXiv]

Simulation-based hypothesis testing of high dimensional means under covariance heterogeneity
with Jinyuan Chang, Chao Zheng and Wen Zhou
Biometrics, 73, 1300-1310, 2017
[DOI] [arXiv] [slides]

Comparing large covariance matrices under weak conditions on the dependence structure and its application to gene clustering
with Jinyuan Chang, Wen Zhou and Lan Wang
Biometrics, 73, 31-41, 2017
[DOI] [arXiv]

Guarding against spurious discoveries in high dimensions
with Jianqing Fan
Journal of Machine Learning Research, 17(203), 1-34, 2016
[DOI] [arXiv] [slides]

Nonparametric covariate-adjusted regression
with Aurore Delaigle and Peter Hall
The Annals of Statistics, 44, 2190-2220, 2016

Cramér-type moderate deviations for Studentized two-sample U-statistics with applications
with Jinyuan Chang and Qi-Man Shao
The Annals of Statistics, 44, 1931-1956, 2016
[DOI] [slides]

Matrix completion via max-norm constrained optimization
with Tony T. Cai
Electronic Journal of Statistics, 10, 1493-1525, 2016

Cramér type moderate deviation theorems for self-normalized processes
with Qi-Man Shao
Bernoulli, 22, 2029-2079, 2016

Nonparametric and parametric estimators of prevalence from group testing data with aggregated covariates
with Aurore Delaigle
Journal of the American Statistical Association, 110, 1785-1796, 2015

Necessary and sufficient conditions for the asymptotic distributions of coherence of ultra-high dimensional random matrices
with Qi-Man Shao
The Annals of Probability, 42, 623-648, 2014
[DOI] [arXiv] [slides]

A max-norm constrained minimization approach to 1-bit matrix completion
with Tony T. Cai
Journal of Machine Learning Research, 14, 3619-3647, 2013

Review Articles

Principal component analysis for big data
with Jianqing Fan, Qiang Sun and Ziwei Zhu
Wiley StatsRef: Statistics Reference Online, 2018
[DOI] [pdf]

Self-normalization: Taming a wild population in a heavy-tailed world
with Qi-Man Shao
Applied Mathematics-A Journal of Chinese Universities, 32, 253-269, 2017

Editorial Service

2022-Present: Associate Editor, Annals of Statistics
2022-Present: Associate Editor, Annals of Applied Probability
2022-Present: Associate Editor, JRSSB
2020-Present: Associate Editor, Statistics: A Jnl of Theor. & Appl. Stat


2021-Present: Associate Professor, Department of Mathematics, University of California, San Diego
2017-21: Assistant Professor, Department of Mathematics, University of California, San Diego
2015-17: Postdoctoral Research Associate, Department of Operations Research and Financial Engineering, Princeton University
2013-15: Research Fellow, School of Mathematics and Statistics, University of Melbourne