Apratim Dey joined us as Assistant Professor of Statistics and Data Science in July 2026, following a postdoctoral stint at Stanford University, where he also received his Ph.D. in Statistics in 2025 under Professor David Donoho.
Apratim's research interests span AI and machine learning, theoretical and computational statistics, and signal processing, with a particular focus on the intersection of statistical methodology and scientific discovery. A central thread in his research is understanding, at a fundamental level, what it takes to build better datasets, train AI models, and develop the computational tools needed to solve real scientific problems—and, just as critically, to develop the statistical methods required to draw valid scientific conclusions from AI-driven analysis. He believes deeply in the synergy between theory and large-scale computational experimentation. A closely related interest of his is characterizing the algorithms scientists broadly use to extract signal from noise, drawing on theories and tools from high-dimensional statistics, probability, geometry, and physics.
At WashU, Apratim was excited by the wealth of new kinds of datasets and computational questions that departments across campus are exploring. He said, "the still-new Department of Statistics and Data Science at WashU is perfectly poised to participate in interdisciplinary, collaborative science, and nothing can be more exciting for a statistician today." At WashU, he has been exploring collaborative opportunities across both the Danforth and Medical campuses. He aims to be part of a central computational and scientific force in these partnerships, engaging scientists to understand their needs and developing the right methodology.
Sean McGrath is a new Assistant Professor in the Department of Statistics and Data Science at WashU, with a joint appointment in the Bursky School of Public Health. Prior to joining WashU, he held postdoctoral positions at Harvard Medical School and Harvard Pilgrim Health Care Institute, as well as at the Yale School of Public Health. He completed his Ph.D. in Biostatistics at Harvard University in 2024, advised by Professor Rajarshi Mukherjee.
Sean's research focuses on problems in causal inference, semiparametric theory, and data integration. His work in these areas includes statistical theory, method development, and applications. He described a particular interest of his as "understanding when and how one can use flexible statistical and machine learning models to estimate causal effects in a way that still yields valid and efficient inference."
When asked about his decision to come to WashU, Sean shared, "At WashU, I'm looking forward to forming collaborations across the SDS department and the School of Public Health. One reason I joined WashU is that the joint appointment is a unique opportunity to pursue both my statistical methodology work and my applied public health work. I'm also excited about joining a relatively new department where I can help shape its direction. On a personal note, I'm glad to have moved to St. Louis since I have a lot of family in the area."
