
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.
Openings
I will be able to take two or three new PhD students in Fall 2024. In order to work under my supervision, you must first pass the Statistics PhD Qualifying Exam (details here) in August 2024 — I cannot advise students who have not passed this exam. My hope is to have (at least) one new student work on Bayesian methods/algorithms and (at least) one new student work on deep learning problems. Potential projects within these areas include scalable Bayesian computation, generative modeling of non-IID data, causal inference, and competing risks. Information for prospective studentsRecent News
- December 2023: My PhD student Shijie Wang has had the first chapter of his dissertation, “Generative multi-purpose sampler for weighted M-estimation” (co-authored with Minsuk Shin and Jun Liu) accepted for publication in Journal of Computational and Graphical Statistics. Paper
- October 2023: “Scalable high-dimensional Bayesian varying coefficient models with unknown within-subject covariance” (with Mary R. Boland and Yong Chen) has been published in Journal of Machine Learning Research. Paper
- October 2023: New preprint “Sparse high-dimensional linear mixed modeling with a partitioned empirical Bayes ECM algorithm” (with Anja Zgodic, Jiajia Zhang, and Alexander McClain). arXiv
- 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