David Dunson
Arts and Sciences Distinguished Professor of Statistical Science & Mathematics
David Dunson's research focuses on developing statistical and machine learning methodology for analysis and interpretation of complex and high-dimensional data, with a particular emphasis on scientific applications, Bayesian statistics and probability modeling approaches. Methods development and theory is directly motivated by challenging applications in neuroscience, genomics, environmental health, and ecology among others. His work has had a substantial impact, with an H-index of 94. He has received numerous awards, including a gold medal from the US Environmental Protection Agency, the COPSS Presidents' Award given to one outstanding statistician each year, the Mortimer Spiegelman Award given to one outstanding public health statistician each year, a highly cited researcher award from Web of Science, an IMS Medallion lecture, and most recently the G.W. Snedecor Award of the Committee of the Presidents of Statistical Societies (COPSS).
Research Interests
David Dunson is a highly regarded researcher with a profound expertise in mathematics and statistics, particularly in the realm of machine learning. His research interests are centered around statistical science and its practical applications, where he is notably passionate about Bayesian modeling, computational statistics, and machine learning techniques. One of the key areas of his focus lies in developing cutting-edge methodologies to address challenges posed by complex and high-dimensional data in diverse fields, including epidemiology, neurosciences, and ecology. In epidemiology, Dunson leverages machine learning algorithms to analyze large-scale health datasets, enabling a deeper understanding of disease transmission and risk factors. In neurosciences, he employs sophisticated machine learning approaches to glean insights from brain imaging data, unraveling the complexities of brain function and neurological disorders. Moreover, Dunson's contributions in ecology involve using machine learning to investigate intricate ecological patterns and dynamics, aiding conservation efforts and ecological management. Through his interdisciplinary and machine learning-driven approach, David Dunson continues to push the boundaries of statistical science, leaving a lasting impact on various scientific disciplines.
Publications
