Cong Jiang, PhD

Dr. Cong Jiang is an Assistant Professor in the Department of Epidemiology and Biostatistics at the SUNY Downstate School of Public Health. He is a biostatistician specializing in causal inference and machine learning, with research focused on developing statistical methods to improve the design and analysis of clinical and public health studies.

Dr. Jiang’s methodological research addresses questions such as how treatment effects vary across individuals and populations, how evidence can be combined and transported across studies and data sources, and how valid causal conclusions can be drawn when data are incomplete or imperfectly measured. His research interests include heterogeneous causal effects, adaptive treatment strategies, causal mediation analysis, transportability, and data fusion.

His work is closely connected to collaborative research in infectious diseases, particularly HIV and tuberculosis, as well as vaccine research, smoking cessation, and precision medicine. He welcomes collaborations involving complex methodological challenges in clinical trials, observational studies, and multi-source data, particularly when new statistical and machine learning approaches can help address clinically and scientifically meaningful questions.

Dr. Jiang received his PhD in Statistics from the University of Waterloo and completed postdoctoral training at the Université de Montréal and the Harvard T.H. Chan School of Public Health.

For more information about Dr. Jiang’s research, publications, and ongoing projects, please visit his personal academic website.