David B. Dunson
Arts and Sciences Professor of Statistical Science
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.
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
Predicting Treatment Futility in Refractory Diffuse Large B cell Lymphoma awarded by (Statistical Analyst). 2014 to 2015
Bayesian Methods for Assessing Gene by Environment Interactions awarded by National Institutes of Health (Principal Investigator). 2009 to 2015
Nonparametric Bayes Methods for Biomedical Studies awarded by National Institutes of Health (Principal Investigator). 2009 to 2015
Emergence of Cardiometabolic Risk Across the Lifecycle in China awarded by University of North Carolina - Chapel Hill (Principal Investigator). 2013 to 2014
Exome-wide screening for common mutations in lymphoma awarded by National Institutes of Health (Investigator). 2011 to 2013
Transfer and Active Learning for Intent Recognition awarded by Office of Naval Research (Investigator). 2008 to 2012