Rate My Professor Joseph Antonelli

Joseph Antonelli is an associate professor of statistics in the Department of Statistics at the University of Florida. He received a B.S. in Statistics from the University of Florida in 2011, an M.S. in Biostatistics from Harvard University in 2013, and a Ph.D. in Biostatistics from Harvard University in 2015. After completing his doctorate, Antonelli served as a Postdoctoral Research Fellow in the Department of Biostatistics at Harvard T.H. Chan School of Public Health from 2015 to 2018. He joined the University of Florida as an Assistant Professor in the Department of Statistics in 2018, advancing to Associate Professor with tenure in 2025. Prior roles include Statistical Consultant at Brigham and Women’s Hospital and Environmental Statistics Trainee supported by the National Institutes of Health.

Antonelli's research interests encompass Bayesian inference, high-dimensional modeling, causal inference, and environmental statistics, with applications to environmental health and criminology. He serves as an Associate Editor for Bayesian Analysis. His contributions have been recognized with numerous awards, including the 2020 Health Effects Institute Walter A. Rosenblith Young Investigator Award, the 2020 Journal of Speech, Language, and Hearing Research Editors Award for “Parental language input to children with hearing loss: does it matter in the end?”, the 2017 Joint Statistical Meetings Biometrics Section Young Investigators Award for “Doubly robust matching estimators for high dimensional confounding adjustment”, the 2016 International Society for Bayesian Analysis Young Investigator Travel Award, the 2015 Harvard Biostatistics Award for Excellence in Teaching, and the 2014 Eastern North American Region of the International Biometric Society Distinguished Student Paper Award. Notable publications include "Causal Analysis of Air Pollution Mixtures: Estimands, Positivity, and Extrapolation" (The American Journal of Epidemiology, 2024), "Multiple exposure distributed lag models with variable selection" (Biostatistics, 2024), "Heterogeneous causal effects of neighborhood policing in New York City with staggered adoption of the policy" (Journal of the Royal Statistical Society: Series A, 2023), "Estimation and false discovery control for the analysis of environmental mixtures" (Biostatistics, 2022), and "Causal Inference in high dimensions: A marriage between Bayesian modeling and good frequentist properties" (Biometrics, 2022).