David B. Dunson

Arts and Sciences Distinguished Professor
Departments of Statistical Science, Mathematics, and ECE
Curriculum Vitæ

Research Interests
Bayesian statistical and data science methods motivated by complex applications. Ongoing methodologic
research focuses on nonparametric Bayes, latent structure learning, big data, scalable Bayesian inferences,
machine learning, and high-dimensional low sample size problems. An emphasis is on approaches for learning
low-dimensional structure underlying high-dimensional "objects" (images, surfaces, shapes, text, arrays,
) with uncertainty quantification. This work involves inter-discplinary thinking at the
intersection of statistics, mathematics and computer science. Motivation comes from applications in epidemiology,
environmental health, neurosciences, genetics, fertility and other settings (music, fine arts, humanities).

Submitted Papers & Pubs
Google Scholar
Postdoc Add

Recent Press:

Mouse love song research

New Dynamic Optimal Timing (DOT) App for fertility

Economic Graph Challenge

Article in The Atlantic highlighting our fertility research

Recent Student/Postdoc Awards:

Daniele Durante wins 2015 David Byar Award

Vinayak Rao wins 2015 Savage Award for Best Bayesian dissertation

Students and Postdocs

Representative painting

My son's music on youtube