David B. Dunson

David B. Dunson develops statistical and machine-learning methods for complex data, with applications in biodiversity, neuroscience, and health; he earned degrees in mathematics and biostatistics, worked at the National Institute of Environmental Health Sciences, and joined Duke. His work includes robust Bayesian inference, the Lifeplan biodiversity project, and a 2026 Bayesian model for multiview medical data. He received the George W. Snedecor Award in 2021, and as of October 2026 he is Duke’s Arts and Sciences Distinguished Professor of Statistical Science.

Now at: Duke University
Works: 709
Citations: 56,400
h-index: 75
Badges: Wayfarer
Loyal

Publication numbers from OpenAlex, as of 19 October 2026.

Timeline

1994–1997

Mathematics and biostatistics degrees

He earns a mathematics bachelor's degree at Pennsylvania State University in 1994 and a Ph.D. in biostatistics at Emory University in 1997.
1997–2008

From NIEHS to Duke

He works at the National Institute of Environmental Health Sciences from 1997 to 2008, joins Duke as an adjunct associate professor in 2000, and becomes a full-time Duke professor in 2008.
2007

A public health statistics award

He wins the Mortimer Spiegelman Award in 2007, an honor for statisticians who contribute to health statistics.
2019

Robust Bayesian inference

He and Jeffrey Miller publish “Robust Bayesian inference via coarsening” in the Journal of the American Statistical Association in 2019.
2020–2026

Lifeplan and the Snedecor Award

His Lifeplan project, “A Planetary Inventory of Life,” runs from 2020 through 2026 and combines big data with novel statistical methods. He receives the George W. Snedecor Award in 2021, an honor for contributions to statistical theory in biometry.
July 2026

Multiview factor models

He coauthors “Bayesian joint additive factor models for multiview learning,” published in Biometrics in July 2026. Its JAFAR model separates variation shared across data views from view-specific variation and predicts time to labor onset from multi-omics data.
As of October 2026

Duke distinguished professor

As of October 2026, he is Duke’s Arts and Sciences Distinguished Professor of Statistical Science, a position he has held since 2013. His research develops statistical and machine learning methods for complex, high-dimensional data in ecology and biodiversity, neuroscience, environmental health, epidemiology, and genomics.