David B. Dunson
- Arts and Sciences Professor of Statistical Science
- Professor of Statistical Science
- Professor in the Department of Electrical and Computer Engineering (Secondary)
- Faculty Network Member of the Duke Institute for Brain Sciences
Development of Bayesian statistical methods and approaches for uncertainty quantification motivated by applications with complex and high-dimensional data. A particular interest is in high-dimensional low sample size data in which it is necessary to incorporate dimensional reduction through carefully designed prior distributions and challenges arise in efficiently computing posterior approximations. Ongoing focus areas include new algorithms for approximating posterior distributions in big data settings, nonparametric Bayes probability modeling allowing for uncertainty in distributional assumptions, analysis of network data, incorporating physical and geometric prior knowledge in modeling and novel models for dimension reduction for "object data" (functions, tensors, shapes, etc). Primary application areas include genomics, neurosciences, epidemiology, and reproductive studies but with much broader interests in developing new methods motivated by difficult applications (in art, music, radar, imaging processing, etc).
Dunson, DB, Weinberg, CR, Perreault, SD, and Chapin, RE. "Summarizing the motion of self-propelled cells: Applications to sperm motility." Biometrics 55.2 (1999): 537-543.
Dunson, DB, Baird, DD, Wilcox, AJ, and Weinberg, CR. "Day-specific probabilities of clinical pregnancy based on two studies with imperfect measures of ovulation." Human Reproduction 14.7 (1999): 1835-1839. Full Text
Dunson, DB. "Dose-dependent number of implants and implications in developmental toxicity." Biometrics 54.2 (1998): 558-569. Full Text
Dunson, WA, Paradise, CJ, and Dunson, DB. "Inhibitory effect of low salinity on growth and reproduction of the estuarine sheepshead minnow, Cyprinodon variegatus." Copeia 1 (1998): 235-239.
Murray, JS, Dunson, DB, Carin, L, and Lucas, JE. "Bayesian Gaussian Copula Factor Models for Mixed Data." Full Text Open Access Copy
Johndrow, JE, Mattingly, JC, Mukherjee, S, and Dunson, D. "Optimal approximating Markov chains for Bayesian inference." Open Access Copy
Banerjee, A, Dunson, D, and Tokdar, S. "Efficient Gaussian Process Regression for Large Data Sets." Open Access Copy
Cornelis, B, Yang, Y, Vogelstein, JT, Dooms, A, Daubechies, I, and Dunson, D. "Bayesian crack detection in ultra high resolution multimodal images of paintings." Open Access Copy