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About Me:

I am an Assistant Professor in the Dept. of Statistics with affiliation to Institute of Data Science at Texas A&M University. I hold a B.S. of Math in the China Math Base at Shandong University and a M.S. of Math in Dept. of Math at University of Southern California. I received my PhD in the Dept. of Statistics and Applied Probability at UCSB, of Math Subject Classification: 60 – Probability Theory and Stochastic Processes. I hold a one year position as Postdoctoral Research Associate in the Dept. of Applied Math at the Univ. of Washington, Seattle and a three year position as Postdoctoral Research Fellow in the Dept. of Statistics at the University of Michigan, Ann Arbor. (Picture at IMS annual meeting in London, June 2022)

Prior to my PhD study, I worked as software developer / database architect in industry in Los Angeles full-time for about 4 years. I specialize at massive data analysis, parallel computing, and user-friendly platform development with multiple languages: R (advanced R with S4 classes and methods), C, C++, Python, Java, SQL/Transaction SQL, Matlab, SAS (advanced programmer since 2012), etc. I am good at operating systems: Windows, Mac, and Linux, as well as systems interacting manipulations and cloud computing.

My research interest in general is stochastic processes, Markov chains, time series, networks, and machine learning. Specifically, my research interests and expertise, include but are not limited to, the following topics: modern stochastic processes/Markov chains/time series analysis, networks/combinatorics/graphical models, high dimension, stochastic algorithm, Monte Carlo methods, hidden Markov/non-Markov models, and asymptotics. The main application areas of my research are epidemiology and finance.

Recent News:

• 03/2023 With a great pleasure, I started to serve as an invited reviewer for Financial Innovation (Springer), which ranked 8th in finance journals.

• 02/2023 With a great pleasure, from Fall 2023, I am expected to teach the required PhD core course Probability for Statistics (Stat 614) and design the corresponding probability qualification exam.

• 02/2023 I presented at the Virtual Time Series Seminar, founded by Majid Al-Sadoon, Adriana Cornea-Madeira, Dimitris Korobilis, Alessandra Luati, Geert Mesters, Michele Piffer, and Abderrahim Taamouti. Title: High-dimensional parameter learning over non-linear and non-Gaussian time series models. Please subscribe their mail list if you are interested in time series.

• 02/2023 I presented at the Mathematical Physics and Harmonic Analysis Seminar, Dept. of Math, Texas A&M Univ. Title: Mosco Convergence of Dirichlet Forms on Machine Learning Gibbs Measures. Thank you so much for your interest and/or attending that talk! I am so happy that so many people attended.

• 01/2023 With a great honor, I started to serve as an invited reviewer for the Proceedings of the National Academy of Sciences (PNAS), which has H-index 805 and Impact Factor: 12.78 (2021).

• 01/2023 With a great honor, I started to serve as an invited reviewer for Nature Climate Change, which is the No. 1 ranked journal in Environmental Science according to Scimago with Impact Factor: 21.72 (2020).

• 01/2023 With a great honor, I served as a Judge of the Student Paper Competition, ASA Section on Bayesian Statistical Science (SBSS).

• 12/2022 My paper "Multi-dimensional Path-dependent Forward-backward Stochastic Variational Inequalities" is accepted to Set-Valued and Variational Analysis, which is top ranked in 5 Scimago categories in Math & Stat. 

• 12/2022 With a great honor, I started to serve as an invited reviewer for the Journal of the Royal Society Interface, which is top ranked in 6 Scimago categories.