Avi Kenny

Avi Kenny is an Assistant Professor in the Department of Biostatistics and Bioinformatics at Duke University, with a secondary appointment as Assistant Research Professor at the Duke Global Health Institute. His work bridges statistical methodology development with practical applications in global health research, particularly focusing on vaccine trials, cluster randomized trials, and health program evaluations in resource-limited settings.

Dr. Kenny's educational background includes:

• Ph.D. in Biostatistics from the University of Washington (2023)

Dr. Kenny's research program spans several interconnected areas in biostatistics and global health. His primary methodological interests include developing statistical approaches for handling treatment effect heterogeneity in cluster randomized trials, particularly stepped wedge designs, and creating survival analysis methods that incorporate machine learning tools. He has made significant contributions to immune correlates analysis for vaccine trials, developing both theoretical frameworks and practical software tools. His applied work focuses on global health program evaluation, with extensive experience in low-resource settings, particularly from his five years working in Liberia as Director of Research, Monitoring, and Evaluation at Last Mile Health. More recently, he has expanded his research to include studies on psychedelic medicine for mental health conditions and implementation science around community health worker programs.

Analysis of Dr. Kenny's publication record reveals a strong focus on methodological innovations in vaccine trial analysis, particularly immune correlates research, with multiple papers on COVID-19 and HIV vaccine trials. His work consistently bridges theoretical statistical development with practical implementation, often resulting in open-source software tools. He has developed specialized methods for stepped wedge cluster randomized trials and has made significant contributions to survival analysis techniques applicable to HIV cohort studies. His research demonstrates an integration of rigorous statistical methodology with pressing global health questions.

Dr. Kenny leads several research initiatives supported by external funding, including an NIH-funded randomized controlled trial of a novel algorithm for managing lower respiratory tract infections in resource-limited settings (2022-2027). His work with students and collaborators spans both methodological development and applied global health research, with particular emphasis on ensuring statistical rigor in complex trial designs and health program evaluations.

Dr. Kenny has developed several important open-source software packages that implement his methodological contributions, including SimEngine for statistical simulations in R, steppedwedge for analyzing stepped wedge cluster randomized trials, and vaccine for immune correlates analysis of vaccine clinical trial data. These tools have been widely adopted by the research community and represent a significant contribution to making advanced statistical methods accessible to applied researchers.