Photo taken at Sleeping Bear Dunes, Michigan
Photo taken at Sleeping Bear Dunes, Michigan
Email: x@y where x=yun.wei and y=utdallas.edu
Permanent Email: x@y where x=cloudwei and y=umich.edu
Office location: FO 2.604D
I am an Assistant Professor of Statistics at the Department of Mathematical Science, University of Texas at Dallas. I am mainly interested in foundations of AI, data sciences, statistics, and related fields.
I was a postdoc at SAMSI and the Department of Statistical Science at Duke University. My postdoc mentor is firstly Sayan Mukherjee. After Sayan moved to Germany, I also worked with Eric Laber.
I obtained my Ph.D. degree from the program Applied and Interdisciplinary Mathematics at the Department of Mathematics, University of Michigan. Even though the Ph.D. degree is applied mathematics, I am supervised by Alfred Hero from EECS and XuanLong Nguyen from Statistics. I obtained my B.S. degree in Computational Mathematics from Nankai University.
Research Interests
Latent Variable Models, Hierarchical models
Foundations of AI
Reinforcement Learning & Operations Management
High Dimensional Statistics
Bayesian Statistics
I am broadly interested in statistics, optimization, and machine learning. I am looking for motivated PhD students and research interns with backgrounds in mathematics, statistics, operations research, computer science, or other related fields.
Open Positions
If you are already a PhD student at UTD, feel free to drop me an email.
For research intern, feel free to drop me an email with your CV and transcripts.
News
August 2026. I will organize and chair a session titled 'Novel theoretical development in mixture models and latent variable models' in JSM 2026 at Boston, MA. (upcoming)
June 2026. I will give a talk at ICSA 2026 at Arlington, Virginia. (upcoming)
May 2026. I will host Mengxin Wang's seminar talk at UTD. (upcoming)
April 2026. I will host Yifan Hu's visit and seminar talk at UTD. (upcoming)
Feb 2026. Seminar at Texas A&M University Corpus Christi, hosted by Harry Lee.
Jan 2026. New Paper. Our paper "Optimal transport based theory for latent structured models" is available online.
Dec 2025. New Paper. Our paper "A Bayesian approach to learning mixtures of nonparametric components" is available online.
Oct 2025. New Paper. Our paper "Distributional Evaluation of Generative Models via Relative Density Ratio" is available online.
Sep 2025. New version Paper. An updated version of our paper "Minimum $\Phi$-distance estimators for finite mixing measures" is available online.
Jun 2025. New Paper. Our paper "Large Deviations for Sequential Tests of Statistical Sequence Matching" is available online.