# David B. Dunson

- Arts and Sciences Professor of Statistical Science
- Professor of Statistical Science
- 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).

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.
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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.
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Hannah, LA, Powell, WB, and Dunson, DB. "Semiconvex Regression for Metamodeling-Based Optimization." *SIAM Journal on Optimization* 24.2 (January 2014): 573-597.
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Chen, CWS, Dunson, D, Frühwirth-Schnatter, S, and Walker, SG. "Special issue on Bayesian computing, methods and applications." *Computational Statistics and Data Analysis* 71 (2014): 273--.
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Scarpa, B, and Dunson, DB. "Enriched Stick Breaking Processes for Functional Data." *Journal of the American Statistical Association* 109.506 (January 2014): 647-660.
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Xing, Z, Nicholson, B, Jimenez, M, Veldman, T, Hudson, L, Lucas, J, Dunson, D, Zaas, AK, Woods, CW, Ginsburg, GS, and Carin, L. "Bayesian modeling of temporal properties of infectious disease in a college student population." *Journal of Applied Statistics* 41.6 (January 1, 2014): 1358-1382.
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Wade, S, Dunson, DB, Petrone, S, and Trippa, L. "Improving prediction from dirichlet process mixtures via enrichment." *Journal of Machine Learning Research* 15 (January 1, 2014): 1041-1071.

Durante, D, Scarpa, B, and Dunson, DB. "Locally adaptive factor processes for multivariate time series." *Journal of Machine Learning Research* 15 (January 1, 2014): 1493-1522.

Carlson, DE, Vogelstein, JT, Qisong Wu, , Wenzhao Lian, , Mingyuan Zhou, , 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 Bio Medical Engineering* 61.1 (January 2014): 41-54.
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Canale, A, and Dunson, DB. "Nonparametric Bayes modelling of count processes." *BIOMETRIKA* 100.4 (December 2013): 801-816.
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