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

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).

Education & Training
  • Ph.D., Emory University 1997

  • B.S., Pennsylvania State University 1994

Wheeler, MW, Dunson, DB, Pandalai, SP, Baker, BA, and Herring, AH. "Mechanistic Hierarchical Gaussian Processes." Journal of the American Statistical Association 109.507 (July 2014): 894-904. Full Text

Kessler, DC, Taylor, JA, and Dunson, DB. "Learning phenotype densities conditional on many interacting predictors." Bioinformatics (Oxford, England) 30.11 (June 2014): 1562-1568. Full Text

Pati, D, Bhattacharya, A, Pillai, NS, and Dunson, D. "Posterior contraction in sparse Bayesian factor models for massive covariance matrices." The Annals of Statistics 42.3 (June 2014): 1102-1130. Full Text

Lin, L, and Dunson, DB. "Bayesian monotone regression using Gaussian process projection." Biometrika 101.2 (June 1, 2014): 303-317. Full Text

Zhang, J, Jima, D, Moffitt, AB, Liu, Q, Czader, M, Hsi, ED, Fedoriw, Y, Dunphy, CH, Richards, KL, Gill, JI, Sun, Z, Love, C, Scotland, P, Lock, E, Levy, S, Hsu, DS, Dunson, D, and Dave, SS. "The genomic landscape of mantle cell lymphoma is related to the epigenetically determined chromatin state of normal B cells." Blood 123.19 (May 2014): 2988-2996. Full Text

Kundu, S, and Dunson, DB. "Bayes variable selection in semiparametric linear models." Journal of the American Statistical Association 109.505 (March 2014): 437-447. Full Text

Bhattacharya, A, Pati, D, and Dunson, D. "Anisotropic function estimation using multi-bandwidth Gaussian processes." The Annals of Statistics 42.1 (February 2014): 352-381. Full Text

Pati, D, and Dunson, DB. "Bayesian nonparametric regression with varying residual density." Annals of the Institute of Statistical Mathematics 66.1 (February 1, 2014): 1-31. Full Text

Cui, K, and Dunson, DB. "Generalized Dynamic Factor Models for Mixed-Measurement Time Series." Journal of computational and graphical statistics : a joint publication of American Statistical Association, Institute of Mathematical Statistics, Interface Foundation of North America 23.1 (February 2014): 169-191. Full Text

Carlson, DE, Vogelstein, JT, Wu, Q, Lian, W, Zhou, M, Stoetzner, CR, Kipke, D, Weber, D, Dunson, DB, and Carin, L. "Multichannel electrophysiological spike sorting via joint dictionary learning and mixture modeling." IEEE Transactions on Biomedical Engineering 61.1 (January 1, 2014): 41-54. Full Text Open Access Copy