Sudipto Banerjee (born October 23, 1972) is an Indian-American statistician best known for his work on Bayesian hierarchical modeling and inference for spatial data analysis.
Banerjee joined the University of Minnesota, Twin Cities in 2000 as an assistant professor of Biostatistics and was associated with the School of Public Health for 14 years.
There he worked on a number of problems and wrote numerous articles on spatial statistics, developing theory and methods related to Bayesian modeling and inference for geographic data with wide-ranging applications in public and environmental health sciences, ecology, forestry, real estate economics and agronomy.
In another high-profile study, Banerjee was invited to serve on a committee formed by the National Research Council and the National Academy of Sciences in 2015-16 for his expertise in the use of spatial data science in analyzing and synthesizing geographically referenced flood insurance data in devising an affordability framework for Federal Emergency Management Agency (FEMA).
Professor Banerjee contributed with his expertise in spatial data science and GIS technologies within a comprehensive policy framework to ascertain when and where premium increases from the Biggert–Waters Flood Insurance Reform Act of 2012 lose cost effectiveness.