معرفی
Sudipto Banerjee is a Professor and Chair of the Department of Biostatistics at the University of California, Los Angeles (UCLA) Fielding School of Public Health, with secondary appointments in the Department of Statistics & Data Science and the UCLA Institute of the Environment & Sustainability. He is a Senior Associate Dean for Academic Programs at UCLA Fielding School of Public Health.
- Education: PhD in Statistics (University of Connecticut, 2000), M.STAT (Indian Statistical Institute, 1996), BS (Honours) in Environmental Science (University of Calcutta, 1194).
Research Interests: Dr. Banerjee specializes in Bayesian hierarchical modeling, spatial and spatiotemporal statistics, and scalable Gaussian process models for big data. His work bridges spatial data science with public health, focusing on environmental exposures and their health impacts, such as through the Deepwater Horizon (GuLF Study) and Aliso Canyon gas leak projects. He develops computational algorithms for Bayesian inference, including predictive processes, nearest-neighbor Gaussian processes, and meta-kriging, enabling efficient analysis of massive spatial datasets.
Recent Publications emphasize methods for nonstationary spatial covariance, scalable multivariate modeling, and applications in environmental epidemiology. His theoretical contributions include advancing probabilistic frameworks for spatial gradients (wombling) and integrating mechanistic models with machine learning for uncertainty quantification.
Honors and Awards: Recipient of the Jerome Sacks Cross-Disciplinary Award (2024), George Snedecor Award (2019), ASA and IMS Fellowships, and the Mortimer Spiegelman Award (2011). He served as President of the International Society for Bayesian Analysis (2022).
Leadership and Grants: Principal Investigator for over 14 NIH and NSF grants, advancing spatial-temporal methodology and its application to public health. He oversees data analysis for the Aliso Canyon gas leak study and has led exposure assessments in the Deepwater Horizon oil spill projects.
