The Texas A&M University Department of Statistics will host the 2014 H.O. Hartley Memorial Lectures featuring Duke University statistician Dr. David B. Dunson next week.

Dunson, Arts and Sciences Distinguished Professor in the Department of Statistical Science at Duke and an international expert in Bayesian statistics, will present one lecture each afternoon on three consecutive days in celebration of the prestigious annual event honoring the department's founding director.

On Monday, Oct. 13, Dunson will present "Bayes for Big Data" at 4 p.m. in Room 1400 of the Memorial Student Center (MSC) on Texas A&M's main campus. On Tuesday, Oct. 14, Dunson will deliver a second talk, "Wasserstein Posteriors: Robust & Scalable Bayes," at 4 p.m. in Room 457 of the John R. Blocker Building. Finally, on Wednesday, Oct. 15, Dunson will close out the event with "Bayes for Big Tables & Networks," set for 4 p.m. in Room 1400 of the MSC.

All three lectures are free and open to the public, with no RSVPs nor tickets required.

The H.O. Hartley Memorial Lectures were established by the Department of Statistics in 1988 to honor Herman Otto Hartley, who came to Texas A&M in 1963 as a distinguished professor of statistics and founded Texas A&M's Institute of Statistics, serving as its inaugural director until his retirement in 1977. Hartley built his initial faculty of four into a group of 16, directed more than 30 doctoral students, and published more than 75 papers during this period. In addition, he served as president of the American Statistical Association (ASA) in 1979 prior to his death on December 30, 1980.

Dunson, a fellow of both the ASA and the Institute of Mathematical Statistics, received his Ph.D in biostatistics from Emory University in 1997 under the direction of Elizabeth Halloran. He was named full professor in the Department of Statistical Science at Duke in August 2008 and appointed Arts and Sciences Distinguished Professor of Statistics in May 2013.

Dunson's research interests include Bayesian statistical methodology motivated by complex biomedical data and machine learning applications. His ongoing methodological research focuses on nonparametric Bayes, latent variable methods, big data, scalable Bayesian inferences, functional and object data, and dimensionality reduction. Additional emphasis areas include developing adaptive Bayes approaches for "learning" low-dimensional structure underlying high-dimensional "objects," such as images, surfaces, shapes, text, array data and networks -- work that involves interdisciplinary thinking at the intersection of statistics, geometry and computer science. He has written two books, one of which has received more than 13,000 citations, and has published in excess of 260 articles while giving nearly 100 invited talks throughout his distinguished career.

Dunson currently serves as the action editor for the Journal of Machine Learning Research and was co-editor of Bayesian Analysis from 2006-13. He has been an active associate editor for journals such as Biometrika, the Journal of Royal Statistical Society, B and the Journal of the American Statistical Association, Applications and Case Studies. He was recognized with the President's Award from the Committee of the Presidents of Statistical Societies (COPSS) in 2010.

To learn more about the 2014 event or the Hartley Memorial Lectures in general, go to http://www.stat.tamu.edu/about/awards-and-prizes/hartley-memorial-lectures/.


Contact: Shana K. Hutchins, (979) 862-1237 or shutchins@tamu.edu or Dr. Valen E. Johnson, (979) 845-3141 or vjohnson@stat.tamu.edu

Hutchins Shana

  • David B. Dunson

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