Datta, Somnath


  • Office:  CTRB 5225
  • Phone:  352-294-5920
  • Fax:  352-294-5931
  • Email:  somnath.datta@ufl.edu
  • Website: somnathdatta.org

Department of Biostatistics
College of Public Health & Health Professions College of Medicine
University of Florida
2004 Mowry Rd
P.O. Box 117450
Gainesville, FL 32611


  • Ph. D. (1988), Statistics and Probability, Michigan State University, East Lansing.
  • M. Stat. (1985), Mathematical Statistics and Probability, Indian Statistical Institute, Calcutta.
  • B. Stat. (1983), Statistics, Indian Statistical Institute, Calcutta.

Curriculum Vitae

Professional Biography

Somnath Datta received his undergraduate and master’s degrees in statistics from Indian Statistical Institute followed by a doctoral degree in Statistics and Probability from Michigan State University. He joined the Department of Biostatistics at University of Florida as a tenured full professor in July of 2015 under the preeminence initiative.  Prior to that, he was Professor in the Statistics department at the University of Georgia and in the Bioinformatics & Biostatistics department at the University of Louisville.

Over the years, he has published over one hundred and sixty research papers in various peer reviewed Statistics & Biostatistics journals. He develops novel statistical methods for analyzing public health, dental and biomedical data. His collaborative research interests include bioinformatics, spinal cord injury research, plant pathology and informatics based materials science research. His research projects have been supported by grants from the US National Institutes of Health, the National Science Foundation, and the National Security Agency. He is Elected Member of International Statistical Institute, Elected Fellow of American Statistical Association, and Elected Fellow of Institute of Mathematical Statistics. He has served as a director of over 20 doctoral dissertation committees.


  • Biostatistics
  • Bootstrap Methods
  • Causal Inference
  • Compound Decision
  • Analysis of Clustered Data
  • Clustering and Classification
  • Empirical Bayes
  • Genomics
  • Nonparametrics
  • Personalized Medicine
  • Proteomics
  • Rank Tests
  • Survival Analysis
  • Time Series Analysis