Naveennaidu Narisetty

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Personal profile

Personal profile

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.

Research Interests

High Dimensional Data
Model Selection
Bayesian Computation
Functional Data
Quantile-based Inference
Censored Data
Data Depth

Professional Information

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

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

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Research Output

Bayesian model selection for high-dimensional data

Narisetty, N. N., Jan 1 2019, (Accepted/In press) In : Handbook of Statistics.

Research output: Contribution to journalArticle

  • Bayesian Regularization for Graphical Models With Unequal Shrinkage

    Gan, L., Narisetty, N. N. & Liang, F., Jul 3 2019, In : Journal of the American Statistical Association. 114, 527, p. 1218-1231 14 p.

    Research output: Contribution to journalArticle

  • Selection of nonlinear interactions by a forward stepwise algorithm: Application to identifying environmental chemical mixtures affecting health outcomes

    Narisetty, N. N., Mukherjee, B., Chen, Y. H., Gonzalez, R. & Meeker, J. D., Apr 30 2019, In : Statistics in Medicine. 38, 9, p. 1582-1600 19 p.

    Research output: Contribution to journalArticle

  • Skinny Gibbs: A Consistent and Scalable Gibbs Sampler for Model Selection

    Narisetty, N. N., Shen, J. & He, X., Jul 3 2019, In : Journal of the American Statistical Association. 114, 527, p. 1205-1217 13 p.

    Research output: Contribution to journalArticle

  • A New Approach to Censored Quantile Regression Estimation

    Yang, X., Narisetty, N. N. & He, X., Apr 3 2018, In : Journal of Computational and Graphical Statistics. 27, 2, p. 417-425 9 p.

    Research output: Contribution to journalArticle