I am an Assistant Professor of Statistics at the University of South Carolina where I am also a McCausland Faculty Fellow (2023-2026). Prior to joining USC in 2020, I was a postdoc for two years at the University of Pennsylvania. I got 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 worked in industry for five years as an engineer and as a financial software analyst. Here are the links to my CV and Google Scholar. You are also welcome to connect with me on LinkedIn and Twitter.

My research group conducts research in the following areas of statistics and machine learning:
  • methods and scalable algorithms for high-dimensional data
  • deep learning for deep generative models and reinforcement learning
  • Bayesian methodology and computation
  • survival analysis and causal inference
  • clinical trials, drug discovery, GWAS, and other biomedical applications.
Our group develops new methods, theory, algorithms, and software. Are you interested in working with us? More information here!

Recent News

  • September 2023: New preprint “Sparse high-dimensional linear regression of heteroscedastic data with a partitioned empirical Bayes ECM algorithm” (with Anja Zgodic, Jiajia Zhang, Yuan Wang, Chris Rorden, and Alexander McLain). arXiv

  • June 2023: New preprint “Bayesian group regularization in generalized linear models with a continuous spike-and-slab prior.” arXiv

  • June 2023: I received a Big Data Health Science Center Pilot Project grant to develop new methods for matrix completion with applications to computational drug repositioning.

  • May 2023: New preprint “Two-step 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.

News from past years