Faculty Spotlight: Abhirup Datta, PhD, MS
Datta, an associate professor in Biostatistics, develops and applies statistical and machine learning methods to address substantive questions in environmental health, climate sciences, and global health research.
Abhirup Datta, PhD, MS, is an Associate Professor of Biostatistics at the Bloomberg School of Public Health, where he develops and applies statistical and machine learning methods to address substantive questions in environmental health, climate sciences, and global health research.
Datta joined the Bloomberg School in 2016 after completing his PhD from the University of Minnesota, and most enjoys the intellectual and social atmosphere at Hopkins. “Both are phenomenal,” he says.
In 2024 Datta was named an Emerging Leader Award from the Committee of Presidents of Statistical Societies, and in 2025 was elected a Fellow of the American Statistical Association, a prestigious honor that recognizes exceptional contributions to statistical sciences and commitment to advancing the field.
Datta's current research works to address scientific questions in environmental health, climate sciences, ecology, forestry, as well as in global health, using statistical methods. He is particularly interested in is studying the validity of statistical inference when using AI in these problems. There has been an increasing use of AI in both geospatial sciences and global health, he notes, and researchers have found that often the usage is not appropriate. His research focus has been to study the impact of the inappropriate use of AI in these areas and try to correct for the inadequacies of the AI algorithms, by using more data and better algorithms.
Looking ahead, Datta sees an increased adoption of AI in public health. “It is important to understand how appropriate this usage is; and that will differ in every application of AI,” he explains. “I think that harmonizing AI with statistical modeling and bringing in 100 plus years of knowledge of statistical literature,” he adds, “is going to help create the most trustworthy and efficient AI algorithms.”
Datta has taught the Department’s Probability Theory course for the last several years, and this year designed and introduced a new course on AI Methods for Geospatial Data. In addition, he is currently mentoring five students and two post-doctoral fellows. “Working with PhD students and postdocs is one of the most fulfilling aspects of my job. To be part of their careers and contributing to their professional growth is really rewarding.”
