605 E Springfield Ave, Champaign, IL 61820
Fall 2016 – Assistant Professor of Statistics, University of Illinois at Urbana-Champaign, IL.
2011–2016 Graduate Research/Teaching Assistant, University of Michigan, Ann Arbor, MI.
2010–2011 Quantitative Analyst, Nomura Financial Services, Mumbai, India.
High Dimensional Data
I have a broad research interest in methodological, computational and theoretical research in Statistics motivated by substantial applications and interdisciplinary collaborations. Research directions include high dimensional data analysis, model selection, Bayesian computation, large-scale computational models, functional data, and quantile modeling.
PhD, Statistics, University of Michigan, 2016
M.A., Statistics, University of Michigan, 2012
M.S., Statistics w/Distinction, Indian Statistical Institute, Kolkata, 2010
B.S., Statistics w/Honors, Indian Statistical Institute, Kolkata, 2008
Additional Campus Affiliations
Affiliate, Carl R. Woese Institute for Genomic Biology
Honors & Awards
ProQuest Distinguished Dissertation Award, University of Michigan, 2017
Rackham Predoctoral Fellowship, University of Michigan, 2016
Excellence in Teaching Award, University of Michigan, 2015
Best Student Paper Award, Nonparametric Statistics Section, American Statistical Association, 2015
Best Student Paper Award, Statistical Learning and Data Science Section, American Statistical Association, 2014
Outstanding PhD Student Award, University of Michigan, 2012
Wu, T., Narisetty, N. N., & Yang, Y. (2023). Statistical inference via conditional Bayesian posteriors in high-dimensional linear regression. Electronic Journal of Statistics, 17(1), 769-797. https://doi.org/10.1214/23-EJS2113
Benedetti, M. H., Berrocal, V. J., & Narisetty, N. N. (2022). Identifying regions of inhomogeneities in spatial processes via an M-RA and mixture priors. Biometrics, 78(2), 798-811. https://doi.org/10.1111/biom.13446
Mrkvička, T., Myllymäki, M., Kuronen, M., & Narisetty, N. N. (2022). New methods for multiple testing in permutation inference for the general linear model. Statistics in Medicine, 41(2), 276-297. https://doi.org/10.1002/sim.9236
Narisetty, N., & Koenker, R. W. (2022). Censored quantile regression survival models with a cure proportion. Journal of Econometrics, 226(1), 192-203. https://doi.org/10.1016/j.jeconom.2020.12.005
Boss, J., Rix, A., Chen, Y. H., Narisetty, N. N., Wu, Z., Ferguson, K. K., McElrath, T. F., Meeker, J. D., & Mukherjee, B. (2021). A hierarchical integrative group least absolute shrinkage and selection operator for analyzing environmental mixtures. Environmetrics, 32(8), [e2698]. https://doi.org/10.1002/env.2698