David Benkeser

David Benkeser is an Associate Professor in the Department of Biostatistics and Bioinformatics at Emory University. He holds affiliations with the Emory Center for AIDS Research and the Emory/Georgia Tuberculosis Research Advancement Center. His research focuses on applying machine learning and causal inference methodologies to address challenges in vaccine efficacy, infectious disease prevention, and HIV/AIDS research.

Benkeser earned his B.S. and MPH from the University of Georgia, followed by a PhD in Biostatistics from the University of Washington. He teaches advanced courses such as DATA 550 (Data Science Toolkit) and DATA 555 (Current Topics in Data Science).

His research interests span causal inference frameworks, vaccine statistics, and methodological innovations for complex longitudinal data. Notable areas include analyzing immune correlates of protection in vaccine trials, evaluating racial disparities in healthcare expenditures, and developing machine learning tools for personalized treatment rules in global health contexts.

Recent work emphasizes leveraging observational data for vaccine efficacy evaluation and advancing statistical methods to handle nonpositivity and high-dimensional confounding. His articles reflect interdisciplinary collaborations in infectious disease epidemiology, public health policy, and computational biology.

Benkeser has contributed to major trials such as the COVE mRNA-1273 vaccine efficacy study and the ENSEMBLE HIV vaccine trials. His methodological work includes developing the 'HART' algorithm for adaptive regression trees and advocating for rigorous statistical practices in machine learning applications.