Assistant Professor, Department of Mathematics and Statistics
Asymptotic Statistics, Bayesian Variable Selection, Nonparametric Inference.
FB-332 B
IIT Kanpur,
Kanpur 208016
Post-doctoral Associate in Duke University under the supervision of Prof. David Dunson and Prof. Sandeep Dave
PhD in Statistics from Indian Statistical Institute (ISI), 2016., Kolkata under the supervision of Prof. Tapas Samanta
M.Sc. in Statistics, University of Calcutta, 2009 (63.50%).
B.Sc. in Statistics, St. Xavier’s College, University of Calcutta, 2007 (73.25%).
Assistant Professor at Department of Statistics, Bethune College, Kolkata, India for the Bachelors’ program in Statistics from September, 2014 till October, 2016.
Taught two short courses at a workshop on Business Statistics organized by Interdisciplinary Statistical Research Unit, ISI, Kolkata at ISI, Tezpur on December, 2016.
Taught the graduate course ‘STA 611: Introduction to Mathematical Statistics’ in Fall 2017 at Department of Statistical Science, Duke University, USA.
Published Papers
Biswas, M., Mukhopadhyay, M. and Ghosh, A. K. (2014) A distribution-free two sample run test applicable to high-dimensional data. Biometrika, 101(4), 913-926.Mukhopadhyay, M., Samanta, T., Chakrabarti, A. (2015) On consistency and optimality of Bayesian variable selection based on g-prior in normal linear regression models. Annals of the Institute of Statistical Mathematics, 67(5), 963-997.Biswas, M., Mukhopadhyay, M. and Ghosh, A. K. (2015) On some exact distributionfree one-sample tests for high dimension low sample size data. Statistica Sinica, 25, 1421-1435.Mukhopadhyay, M. and Samanta, T. (2017) A mixture of g-priors for variable selection when the number of regressors grows with the sample size. TEST, 26, 377-404.Papers communicated for publication/working papers
Mukhopadhyay, M., and Dutta, S. (2018+) Bayesian variable selection for ultrahighdimensional sparse linear models. Available at http://arxiv.org/abs/1609.06031Mukhopadhyay, M., and Dunson, D. (2018+) Targeted random projection for prediction from high-dimensional features. Available at https://arxiv.org/abs/1712.02445Mukhopadhyay, M., and Bhattacharya, S. (2018+) Bayesian non-parametric variable selection using Gaussian processes.