Yuliang Xu
About me
My recent research focuses on the distributional evaluation of generative models for scientific data generation, especially synthetic microbiome data generation and evaluation.
Previously, I was a postdoctoral researcher advised by Prof. Li Ma in the Department of Statistics and Data Science Institute at the University of Chicago (July 2025–June 2026), and in the Department of Statistical Science at Duke University (July 2024–June 2025). I obtained my Ph.D. in Biostatistics from the University of Michigan, advised by Prof. Jian Kang.
During my time at Michigan, I also collaborated with Prof. Florian Gunsilius. I received my B.S. in Mathematics and Applied Mathematics from South China University of Technology in 2017 and my M.S. in Statistics from the University of Waterloo in 2019.
Email: yxu296@jh.edu (work)
yuliangx@umich.edu (permanent)
Research interests
Theory and methods
- Generative models
- Nonparametric Bayesian statistics
- Optimal transport
- Causal inference
Applications and data
- Brain imaging (volumetric fMRI)
- Microbiome data (counts and relative abundances)
- DNA sequencing data
Education
- Ph.D. in Biostatistics, University of Michigan, Ann Arbor, MI, 2024
- M.S. in Statistics, University of Waterloo, Waterloo, ON, 2019
- B.S. in Mathematics and Applied Mathematics, South China University of Technology, Guangzhou, China, 2017
Employment
- Assistant Professor, Department of Applied Mathematics and Statistics; secondary appointment in Biostatistics, Johns Hopkins University, starting July 2026
- Postdoctoral Researcher, Department of Statistics and Data Science Institute, University of Chicago, July 2025–June 2026
- Postdoctoral Researcher, Department of Statistical Science, Duke University, July 2024–June 2025