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Education

  • Ph.D. in Statistics, Purdue University, West Lafayette, IN. (2009 - 2014)
    • Dissertation Topic: “Some Theoretical and Methodological Aspects of Multiple Testing, Model Selection and Related Areas"
    • Ph.D. advisor: Prof. Jayanta K. Ghosh and Prof. Michael Yu Zhu.
  • B.Stat and M. Stat, Indian Statistical Institute, Kolkata, India. (2003-2008)
    • Dissertation Title: “Efficiency Versus Robustness - An Weighted Likelihood Equation Approach".
    • Advisor: Prof. Ayanendranath Basu.

Awards and Honors

  • National and International:
    • NSF CAREER Award (2025). Division of Mathematical Sciences. National Science Foundation. NSF-DMS-2443282.
    • Dayanand Naik award from the ASA-VA chapter (Virginia chapter of American Statistical Association). 2023.
      ‘The Dayanand Naik award recognizes an individual (who works, or resides in Virginia, during the time of the award) for outstanding research contributions and service to the Commonwealth of Virginia in statistics and related fields.’
    • Robert and Sandra Connor Endowed Faculty Fellowship, University of Arkansas, 2018-19.
      News article.
    • William J. Studden Publication Award for an outstanding publication in a mathematical
      statistics journal, 2013, Department of Statistics, Purdue University.
    • Honorable Mention Award for Best Theoretical Poster at the O’Bayes 2013: The Tenth
      International Workshop on Objective Bayesian Statistics, December 15-19, Durham, U.S.A.
    • Competitive Travel Awards:
      • 19th IMS Meeting of New Researchers in Statistics and Probability, 2016
      • International Indian Statistical Association 2016 Conference
      • ASA-Kutner faculty poster session at the SRCOS 2016 Summer Research Conference
      • O-Bayes 2013 : The Tenth International Workshop on Objective Bayesian Statistics
    • Miscellaneous:
      • Award for Academic Excellence, Indian Statistical Institute, Kolkata, 2008.
      • Ranked 8th and 10th in State Level Joint Entrance Examination in Engineering and Medicine (out of approximately two hundred thousand students), 2003.

Professional Experience

  • Spring 2021 - now, Department of Statistics, Virginia Tech.
    • STAT 45404/5504G: Multivariate Statistics.
    • CMDA 2006. Integrated Quantitative Science (Statistics part).
    • CMDA 2014. Data Matter. Undergraduate course on exploring different kinds of data (numerical, qualitative, text and image).
    • STAT 5525. Data Analytics. Graduate course on different tools and techniques for drawing meaningful inference from data, with a comprehensive review of popular Statistics/ML methods.
    • CMDA 4654: Intermediate Data Analytics and ML: Undergraduate course on popular tools for analyzing data and modern Statistical and ML methods.

High-dimensional data, shrinkage prior, sparse signal recovery, structure learning, change point estimation, Compositional data, Grouped covariates, nonparametric Bayes, Cancer genomics, Microbiomics, Ecology, Crime forecasting.

For a full and up-to-date list of publications, please check the Google scholar profile: https://scholar.google.com/citations?user=_wA03WkAAAAJ&hl=en

Five Selected Papers

  1. Datta, J.∗ , and Ghosh, J. K. (2013), “Asymptotic Properties of Bayes Risk for the Horseshoe Prior". Bayesian Analysis 8(1), 111-132.
  2. Datta, J.∗ and Dunson, D. B. (2016), “Bayesian inference on quasi-sparse count data", Biometrika, 103 (4): 971-983.
  3. Bhadra, A., Datta, J.∗, Polson, N. G., & Willard, B. T (2019), (*alphabetical), “Lasso Meets Horseshoe – A Survey". Statistical Science, 34(3), 405-427
  4. Boss, J., Datta, J., Wang, X., Park, S., Kang, J., Mukherjee, B. (2023), “Group Inverse-Gamma Gamma Shrinkage for Sparse Regression with Block-Correlated Predictors". Bayesian Analysis, 1(1), 1-30.
  5. Sagar K. N., Banerjee, S., Datta, J., and Bhadra A. (2024), “Precision Matrix Estimation under Horseshoe-like Penalty". Electronic Journal of Statistics. 18 (1), 1-46. https://doi.org/10.1214/23-EJS2196.

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