I have joined Uber as an applied scientist. I obtained my Ph.D. in statistics from University of California, San Diego, advised by Professor Wen-Xin Zhou. Prior to that, I got my B.S. in Mathematics from Fudan University and M.S. in Statistics from University of Michigan, Ann Arbor.

My research projects cover:

- Statistical learning with growing (intrinsic) dimensionality using empirical process theory
- Computationally efficient quantile regression via a kernel smoothing mechanism
- Huber-type robustification for estimation, regression and multiple inference

I'll be broadly working on machine learning and causal inference, and I'm open to collaboration.

Profile: GitHub page | Google Scholar | Dissertation

- A unified algorithm for penalized convolution smoothed quantile regression (2022+), with Rebeka Man, Kean Ming Tan and Wen-Xin Zhou. Paper
- Scalable estimation and inference for censored quantile regression process (2022+), with Xuming He, Kean Ming Tan and Wen-Xin Zhou.

*The Annals of Statistics*, to appear.

Paper | Supplement | Code - Smoothed quantile regression with large-scale inference (2021+), with Xuming He, Kean Ming Tan and Wen-Xin Zhou.

*Journal of Econometrics*, to appear.

Paper | Package - Multiplier bootstrap for quantile regression: Non-asymptotic theory under random design (2021), with Wen-Xin Zhou.

*Information and Inference: A Journal of the IMA*,**10**, 813-861.

Paper | Code - FarmTest: An R package for factor-adjusted robust multiple testing (2020), with Koushiki Bose, Jianqing Fan, Yuan Ke and Wen-Xin Zhou.

*The R Journal*,**12**, 372-387.

Paper | Package - Iteratively reweighted ℓ
_{1}-penalized robust regression (2021), with Qiang Sun and Wen-Xin Zhou.

*Electronic Journal of Statistics*,**15**, 3287-3348.

Paper | Package

- Math 282B, Applied Statistics.
- Math 281C, Mathematical Statistics. Spring 2020 | Spring 2022
- Math 281A, Mathematical Statistics. Fall 2019

- Math 189, Data Analysis and Inference.
- Math 185, Introduction to Computational Statistics.
- Math 181B, Introduction to Mathematical Statistics II.
- Math 181A, Introduction to Mathematical Statistics I.
- Math 180B, Introduction to Stochastic Processes I.
- Math 180A, Introduction to Probability.
- Math 20E, Vector Calculus.
- Math 11, Calculus-Based Introductory Probability and Statistics.
- Math 10B, Calculus II.

- Professors in my committee: Ery Arias-Castro, Dimitris N. Politis, Jason Schweinsberg and Yixiao Sun
- Professors I've been fortunate to work with: Xuming He, Jian Kang, Yuan Ke, Qiang Sun, Kean Ming Tan, Vivien Yin(intern mentor at Mayo Clinic), Zhiliang Ying(undergraduate thesis advisor)