I joined the Department of Statistics at the University of South Carolina as an Assistant Professor in 2020. From 2018 to 2020, I was a postdoc at the University of Pennsylvania. I earned my PhD in Statistics from the University of Florida, my MS in Applied Mathematics from the University of Massachusetts Amherst, and my BA from Cornell University. Prior to my career in academia, I also worked in industry for five years as an engineer and as a financial software analyst.

My research group conducts research in the following areas of statistics and machine learning:
  • methods and scalable algorithms for high-dimensional data (big p and/or big n)
  • deep learning, especially deep generative models and deep reinforcement learning
  • Bayesian methodology and computation
  • survival analysis and causal inference.
Our research is primarily motivated by addressing “big data” challenges in contemporary biomedical and public health problems such as genome-wide association studies, computational drug repositioning, and analysis of electronic health records. We develop methods and theory, as well as algorithms for harnessing the full potential of high-performance computing.

My CV is attached here. You can also find me on Twitter, LinkedIn, and Google Scholar.

Recent News     (Past News)

  • May 2023: New preprint “Mixed-type multivariate Bayesian sparse variable selection with shrinkage priors” (with Shao-Hsuan Wang and Hsin-Hsiung Huang). arXiv

  • May 2023: My undergraduate student and collaborator Hung-Tien Huang has graduated with his BS in Computer Science from USC and will join University of North Carolina-Chapel Hill this fall for his PhD in Computer Science.

  • April 2023: My PhD student Shijie Wang has won the James D. Lynch Graduate Student Research Award, an award given annually by the USC Statistics Department to one graduate student who has excelled in research.

  • March 2023: My co-author Qingyang Liu has successfully defended his PhD dissertation, “Advancements in Parametric Modal Regression” and will join Texas A&M University as a postdoc in Statistics.

  • February 2023: My PhD student Shijie Wang has passed his PhD dissertation proposal, “New Deep Learning Approaches to Classical Statistical Models.” My students Shijie Wang and Zile Zhao also received summer internships as Machine Learning Data Scientist at Bayer and Biostatistician at Sanofi.

  • January 2023: New preprint “Generative Quantile Regression with Variability Penalty” (with Shijie Wang and Minsuk Shin). arXiv

  • January 2023: I have been selected as a McClausland Faculty Fellow. This selective fellowship supports early-career USC College of Arts and Sciences faculty who are rising stars in their academic disciplines and committed, creative teachers.

Information for prospective students