Speaker：Xiaoquan (William) Wen （University of Michigan）

Venue: 智华楼109

Time: June 19, 2024 10:00 -- 11: 00

Abstract: 

The increasing availability of multimodality genomic data makes exploring molecular mechanisms of complex diseases feasible. In this talk, I will present some of our recent progress in probabilistic modeling of multiple types of genetic, molecular, and complex trait data. I will focus on how the context of the scientific problems leads to the natural formulation of the statistical problems and their probabilistic solutions. I will discuss future challenges and the required skill set for current and next-generation researchers in genomic data science. I will give a general introduction to the graduate program at the Michigan Biostatistics and other ongoing data science research activities at the University of Michigan.

Biography:

Xiaoquan (William) Wen is a professor in the Department of Biostatistics at the University of Michigan. received his PhD in Statistics from the University of Chicago in 2011 and joined the faculty at the University of Michigan in the same year. His current research interests include topics in Bayesian model comparison, Bayesian multiple hypothesis testing and probabilistic graphical models. In applied field, he is particularly interested in seeking statistically sound and computationally efficient solutions to scientific problems in areas of genetics and functional genomics.