Yanxun Xu
I am an Associate Professor and Joseph & Suzanne Jenniches Faculty Scholar in the Department of Applied Mathematics and Statistics at Johns Hopkins University. My research interests lie in developing Bayes theory and methods for a board range of problems, such as reinforcement learning, high-dimensional data analysis, nonparametric statistics, and uncertainty quantification. I also develop new statistical and machine learning methods for various applications, including electronic health records, dynamic treatment regimens, cancer genomics, early detection of Alzheimer’s disease, mental health in people with HIV, early-phase clinical trial designs, and material engineering. My research has been continuously funded by NSF, NIH, and industries.
Other Affiliations:
- Adjunct Associate Professor, Division of Biostatistics and Bioinformatics at Johns Hopkins School of Medicine.
- Faculty member at The Johns Hopkins Mathematical Institute for Data Science (MINDS).
- Faculty member at The Johns Hopkins Institute for Data Intensive Engineering and Science (IDIES).
- Affiliated faculty at The Johns Hopkins Institute for Computational Medicine (ICM).
News:
- Congratulations to PhD student Dapeng Yao on winning the 2024 JSM Student Paper Competition from the ASA Section on Bayesian Statistical Science (SBSS) for the paper “Bayesian Sparse Gaussian Mixture Model in High Dimensions.”
- Congratulations to PhD student Mao Hong on winning the 2024 JSM Student Paper Competition from the ASA Nonparametric Sections for the paper “A Policy Gradient Method for Confounded POMDP.”
- Congratulations to PhD student Zhiyue Zhang on winning the 2024 JSM Student Paper Competition from the ASA section on Lifetime Data Science (LiDS) for the paper “Attentive Joint Model of Longitudinal Data, Survival, and Recurrent Events with Concurrent Latent Structure.”
Openings:
Postdoc and Graduate student research assistant positions are available until filled. If you are interested in these positions, please email your CV to yanxun.xu[AT]jhu[DOT]edu.