I am an Assistant Professor of Mathematics and Statistics at Washington University in St. Louis. I received my Ph.D. degree in statistics at the University of Chicago in 2018. My Ph.D. adviser is Prof. Wei Biao Wu. Prior to graduate school, I obtained my B.S. in mathematics at Tsinghua University in 2013.

I am intersted in high dimensional data analysis, time series, statistical learning theory.

Teaching

Paper

1. Stability and asymptotics for autoregressive processes, 2016
   Likai Chen and Wei Biao Wu, Electronic Journal of Statistics, Vol. 10, 3723-3751, 2016. [pdf]
2. Concentration inequalities for empirical processes of linear time series, 2018
   Likai Chen and Wei Biao Wu, Journal of Machine Learning Research, 18(231):1-46, 2018. [pdf]
3. Testing for trends in high-dimensional time series, 2019
   Likai Chen and Wei Biao Wu, Journal of the American Statistical Association, 2019, Vol. 114, No. 526, 869-881: Theory and Methods. [pdf]
4. Dynamic semiparametric factor model with structural breaks, 2020
   Likai Chen, Weining Wang and Wei Biao Wu, Journal of Business and Economic Statistics, 2020, Vol. 00, No. 0, 1-15. [pdf]
5. Inference of break points in high-dimensional time series
   Likai Chen, Weining Wang and Wei Biao Wu, Journal of the American Statistical Association, 2021, Vol. 00, 1-13 [pdf]
6. Sparse nonlinear vector autoregressive models
   Yuefeng Han, Likai Chen and Wei Biao Wu, Submitted in Journal of Machine Learning Research. [pdf]
7. Estimation of nonstationary nonparametric regression model with multiplicative structure
   Likai Chen, Ekaterina Smetanina and Wei Biao Wu, Econometrics journal, 2021, Vol. 00, pp. 1–39. [pdf]
8. Change point detection for high-dimensional time series based on maxima of Gaussian processes
   Likai Chen, Jia He, Maggie Cheng and Wei Biao Wu, Submitted in ICASSP [pdf]
9. MicrobiomeCensus: Estimating Human Population Sizes from Wastewater Samples Based on Inter-Individual Variability in Gut Microbiomes
   Fangqiong Ling, Likai Chen, Lin Zhang, Xiaoqian Yu, Claire Duvallet, Siavash Isazadeh, Chengzhen Dai, Shinkyu Park, Katya Frois-Moniz, Fabio Duarte, Carlo Ratti, and Eric J. Alm . PLOS Comp Bio. [pdf]
10. 
    Recursive Quantile Estimation:Non-Asymptotic Confidence Bounds
    Likai Chen, Georg Keilbar and Wei Biao Wu, Under review in Journal of Machine learning research [pdf]
11. $\ell^2$ Inference for Change Points in High-Dimensional Time Series via a Two-Way MOSUM
    Jiaqi Li, Likai Chen, Weining Wang and Wei Biao Wu, Submitted in Annals of statistics [pdf]

Invited Talk

1. Statistical Learning for Time Dependent data
   Michigan State University, Oct 2018,
   University of Illinois Urbana-Champaign, March 2018,
   Northwestern University, Feb 2018.
2. Concentration inequalities for empirical processes of linear time series,
   INFORMS Applied Probability Society Conference, 2017.
3. Testing for trends in high-dimensional time Series,
   ICSA Applied Statistics Symposium, 2017.

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