David B. Dunson

David B. Dunson

Arts and Sciences Distinguished Professor of Statistical Science

External address: 
218 Old Chemistry Bldg, Durham, NC 27708
Internal office address: 
Box 90251, Durham, NC 27708-0251
(919) 684-8025


Development of novel approaches for representing and analyzing complex data.  A particular focus is on methods that incorporate geometric structure (both known and unknown) and on probabilistic approaches to characterize uncertainty.  In addition, a big interest is in scalable algorithms and in developing approaches with provable guarantees.

This fundamental work is directly motivated by applications in biomedical research, network data analysis, neuroscience, genomics, ecology, and criminal justice.   

Education & Training

  • Ph.D., Emory University 1997

  • B.S., Pennsylvania State University 1994

Selected Grants

Probabilistic learning of structure in complex data awarded by Office of Naval Research (Principal Investigator). 2017 to 2020

New methods for quantitative modeling of protein-DNA interactions awarded by National Institutes of Health (Co Investigator). 2015 to 2020

An Integrated Nonparametric Bayesian and Deep Neural Network Framework for Biologically-Inspired Lifelong Learning awarded by Defense Advanced Research Projects Agency (Co Investigator). 2018 to 2020

Network motifs in cortical computation awarded by University of California, Los Angeles (Principal Investigator). 2016 to 2019

Nonparametric Bayes Methods for Big Data in Neuroscience awarded by National Institutes of Health (Mentor). 2014 to 2019

Bayesian learning for high-dimensional low sample size data awarded by Office of Naval Research (Principal Investigator). 2014 to 2017

NCRN-MN:Triangle Census Research Network awarded by National Science Foundation (Co Investigator). 2011 to 2016

Bayesian Methods for High-Dimensional Epidemiologic Data awarded by University of North Carolina - Chapel Hill (Principal Investigator). 2011 to 2016


Badea, Alexandra, et al. “Identifying Vulnerable Brain Networks in Mouse Models of Genetic Risk Factors for Late Onset Alzheimer's Disease.Front Neuroinform, vol. 13, 2019, p. 72. Pubmed, doi:10.3389/fninf.2019.00072. Full Text

Strawn, N., et al. “Erratum: Finite sample posterior concentration in high-dimensional regression (Information and Inference (2015) 3 (103-133) DOI: 10.1093/imaiai/iau003).” Information and Inference, vol. 4, no. 1, Jan. 2015. Scopus, doi:10.1093/imaiai/iau008. Full Text

Strawn, N., et al. “Finite sample posterior concentration in high-dimensional regression.” Information and Inference, vol. 3, no. 2, Jan. 2014, pp. 103–33. Scopus, doi:10.1093/imaiai/iau003. Full Text