Long Nguyen

Professor of Statistics, Department of Statistics, University of Michigan
Director of Master's programs in Statistics

Other affiliations:
Professor of EECS, Department of Electrical Engineering and Computer Science (courtesy appt)
Faculty member, Michigan Institute for Data Science
Long-term member, Vietnam Institute for Advanced Study in Mathematics

Email: xuanlong@umich.edu
Office: 461 West Hall, Phone: 734-763-3499, Fax: 734-763-4676

Mail Address: 439 West Hall, 1085 South University, Ann Arbor, MI 48109-1107

[Research] [Teaching] [Students] [Publications]

Students in the Master's programs in Statistics: Questions about specific course work should be directed to the advising team (email address: stat-ms-ad@umich.edu) or to your assigned faculty advisor. Please go to this page to this page set up an appointment with me or other advisors. Students in the dual Master's program are welcome to sign up for an appointment with me.

Prospective PhD students: Please consider applying to Michigan and thank you for your interest. Admissions decision is made a graduate admissions committee, please see this link for further information.

Research interests

Editorial boards

Synopsis: Statistical inference and learning is the computational process of turning data into statistics, prediction and understanding. I work with richly structured data, such as those extracted from texts, images and other spatiotemporal signals.

I am particularly interested in a field in statistics known as Bayesian nonparametrics, which provides a fertile and powerful mathematical framework for the development of many computational and statistical modeling ideas. The spirit of Bayesian nonparametric statistics is to enable the kind of inferential procedures according to which both the statistical modeling and computational complexity may adapt to increasingly large and complex data patterns in a probabilistically graceful and effective way. In this framework, stochastic processes and random measures, along with latent variable models such as mixture, hierarchical and graphical models figure prominently. My students and I seek to understand the interaction between statistical inference and the theory of optimal transport that arises in the learning of complex hierarchical models and spatiotemporal and functional patterns.

My motivation for all this came originally from an early and sustained interest in machine learning. A primary focus in our machine learning research is to develop more effective inference algorithms using variational, stochastic and geometric viewpoints.

Students [selfie in deserted Niagara Falls in November'16] [on a Phở day, March 2018] [@Ashley's] [in the time of COVID-19, May 2020]

Former PhD students and postdocs Master's students Undergraduate honor thesis advisees Visitors

Some collaborative projects and links

Selected talk slides

"XuanLong Nguyen" is used in my English publications. The Vietnamese name is Nguyễn Xuân Long