Jyotishka Datta

Jyotishka Datta is an Assistant Professor in the Department of Statistics at Virginia Polytechnic Institute and State University (Virginia Tech). Previously, he served as an Assistant Professor at the University of Arkansas (2016–2020) and completed a postdoctoral fellowship at Duke University and SAMSI. He holds a Ph.D. from Purdue University and degrees from the Indian Statistical Institute.

His research focuses on Bayesian methodology for high-dimensional data, including shrinkage priors, sparse signal recovery, and applications in genomics, ecology, and crime forecasting. Notable contributions include work on Horseshoe priors and their extensions, as well as interdisciplinary projects in cancer genomics and public health.

Key awards include the NSF CAREER Award (2025), the Robert and Sandra Connor Endowed Faculty Fellowship (2018–19), and the William J. Studden Publication Award (2013). His work bridges statistical theory with practical applications, including collaborations in oncology and environmental science.

Recent articles explore Bayesian shrinkage methods, compositional data analysis, and applications in auditory neuroscience. Ongoing projects involve heavy-tailed priors for robust inference in astronomy and machine learning. He teaches courses in data analytics and statistical theory.