Sudipto Banerjee


  • PhD, Statistics, University of Connecticut, Storrs, CT, 2000
  • M.STAT, Indian Statistical Institute, Calcutta, India, 1996
  • BS (Honours), Presidency College, Calcutta, India, 1994

Research Expertise

  • Statistical modeling and analysis of geographically referenced datasets
  • Bayesian statistics (theory and methods) and hierarchical modelling
  • Statistical computing and related software development

Honors and Awards

  • 2005, Inductee: Pi Chapter of Delta Omega National Honor Society.
  • 2009, Abdel El Sharaawi Young Researcher Award from The International Environmetrics Society.
  • 2010, Elected member, International Statistical Institute.
  • 2011, Mortimer Spiegelman Award from the Statistics Section of the American Public Health Association.
  • 2012, Elected Fellow of the American Statistical Association (ASA).
  • 2012, International Indian Statistical Association's Young Researcher Award.
  • 2015, Presidential Invited Address, Western North American Regional (WNAR) Meeting of the International Biometric Society.
  • 2015, Elected Fellow of the Institute of Mathematical Statistics (IMS).
  • 2015, Distinguished Achievement Medal from ASA Section on Statistics and the Environment.
  • 2017, ASA Outstanding Application Award.
  • 2018, Elected Fellow of the International Society for Bayesian Analysis (ISBA).
  • 2019, George W. Snedecor Award from the Committee of Presidents of Statistical Societies (COPSS).
  • 2020, Elected Fellow of the American Association for the Advancement of Science (AAAS).
  • 2021, President-Elect of the International Society for Bayesian Analysis.

Selected Recent Publications

  • Alaimo Di Loro, P., Mingione, M., Lipsitt, J., Batteate, C.M., Jerrett, M.B. and Banerjee, S. (in press). Bayesian hierarchical modeling and analysis for physical activity trajectories using wearable devices data. Annals of Applied Statistics. DOI: In process.
  • Halder, A., Banerjee, S. and Dey, D.K. (in press). Bayesian modeling with spatial curvature processes. Journal of the American Statistical Association. DOI .
  • Gao, L., Banerjee, S. and Ritz, B. (in press). Spatial difference boundary detection for multiple outcomes using Bayesian disease mapping. Biostatistics. arxiv and DOI .
  • Dey, D., Datta, A. and Banerjee, S. (2022). Graphical Gaussian process models for highly multivariate spatial data. Biometrika, 109, 993--1014. arxiv and DOI
  • Banerjee, S. (2022). Discussion of "Measuring housing vitality from multi-source big data and machine learning”. Journal of the American Statistical Association, 117, 1063–1065. DOI .
  • Peruzzi, M., Banerjee, S. and Finley, A.O. (2022). Highly scalable Bayesian geostatistical modeling via meshed Gaussian Processes on partitioned domains. Journal of the American Statistical Association, 117, 969--982. arxiv and DOI
  • Zhang, L. and Banerjee, S. (2022). Spatial factor modeling: A Bayesian Matrix-Normal approach for misaligned data. Biometrics, 78, 560--573. arxiv and DOI
  • Tang, W., Zhang, L. and Banerjee, S. (2021). On identifiability and consistency of the nugget in Gaussian spatial process models. Journal of the Royal Statistical Society: Series B (Methodology), 83, 1044--1070. arxiv and DOI
  • Abdalla, N., Banerjee, S., Ramachandran, G. and Arnold, S. (2020). Bayesian state space modeling of physical processes in industrial hygiene. Technometrics, 62, 147--160. arxiv and DOI
  • Finley, A.O., Datta, A., Cook, B.C., Morton, D.C. Andersen, H.E. and Banerjee, S. (2019). Efficient algorithms for Bayesian nearest-neighbor Gaussian processes. Journal of Computational and Graphical Statistics, 28, 401--414. arxiv and DOI
  • Guhaniyogi, R. and Banerjee, S. (2018). Meta-Kriging: Scalable Bayesian modeling and inference for massive spatial datasets. Technometrics, 60, 430--444. DOI