Long Nguyen

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

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

Other affiliations:
Department of Electrical Engineering and Computer Science (by courtesy)
Michigan Institute for Data Science

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

Students in the Applied Master's program: If you have questions about specific course work, please send email to the advising team (email address: stat-ms-ad@umich.edu) or set up an appointment with me or other advisors.

Prospective PhD students: Thank you for your interest. Admissions decision is made a graduate admissions committee, please see this link for further information. My apology if I am unable to respond to your enquiry due to the large volume of such emails.

Research interests

Statistical inference 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.

In recent years I have gravitated toward 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 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 motivation for all this came originally from an interest in machine learning, which continues to be a major source of research interest. A primary focus in my machine learning research is to develop more effective inference algorithms using variational, stochastic and geometric viewpoints.

A biased sample of papers

Selected talk slides

Students [group selfie]

Former students, postdocs and visitors

Bio [blurb]


Last updated on September 7, 2015 by XuanLong Nguyen (Nguyễn Xuân Long)