Research Publications

Please visit my Google Scholar page for a chronological indexing of papers. Below the papers are arranged according to the different sub-topics I have worked on.

High-dimensional Predictive Inference

  1. Mukherjee G and Johnstone IM. Exact minimax estimation of the predictive density in sparse Gaussian models. Annals of Statistics, 2015. R-Code: click here.

  2. Mukherjee G and Johnstone IM. On Minimax Optimality of Sparse Bayes Predictive Density Estimates. Annals of Statistics, 2022, Vol. 50, No. 1, 81-106.

  3. Gangopadhyay U and Mukherjee G. On Discrete Priors and Sparse Minimax Optimal Predictive Densities.Electronic Journal of Statistics, 2021, Vol. 15, No. 1, 1636-1660.

  4. George E, Mukherjee G and Yano K. Optimal Shrinkage Estimation of Predictive Densities under alpha–divergences. Bayesian Analysis, 2021, 16, Number 4, pp. 1139-1155.

Inference under heterogeneity

  1. Banerjee T, Bhattacharya B and Mukherjee G. A nearest-neighbor based nonparametric test for viral remodeling in heterogeneous single-cell proteomic data. Annals of Applied Statistics, 2020; R-package: TRUH.

  2. Radchenko P and Mukherjee G. Convex clustering via L1 fusion penalization. Journal of the Royal Statistical Society: Series B; 2017. R-Code: click here; Also, See R-package: fusionclust

  3. Banerjee T, Mukherjee G and Radchenko P. Feature Screening in Large Scale Cluster Analysis. Journal of Multivariate Analysis, 2017. R-Code: COSCI Algorithm; Also, See R-package: fusionclust

  4. Banerjee T, Bhattacharya B and Mukherjee G. Bootstrapped Edge Count Tests for Nonparametric Two-Sample Inference Under Heterogeneity, Submitted, 2023.

  5. Karmakar B, Kwon O, Mukherjee G and Siddharth S. A Backfitting based MCEM Algorithm for Scalable Estimation in Multinomial Probit Model with Multilayer Network Linkages. Submitted, 2023.

  6. Bhuyan R, Javanmard A, Kim S, Mukherjee G, Rossi R, Yu T and Zhao H. Structured Dynamic Pricing: Optimal Regret in a Global Shrinkage Model. Submitted, 2023.

Empirical Bayes Theory & Methods

  1. Brown LD, Mukherjee G and Weinstein A. Empirical Bayes Estimates for a 2-Way Cross-Classified Additive Model. Annals of Statistics, Vol 46, No 4 (2018), 1693-1720.

  2. Banerjee T, Liu Q, Mukherjee G and Sun W. A General Framework for Empirical Bayes Estimation in the Discrete Linear Exponential Family. Journal of Machine Learning Research, 2021. R-code: NPEB

  3. Gang B, Mukherjee G and Sun W. Large-Scale Shrinkage Estimation under Markovian Dependence. Book Chapter in IISA Series on Statistics and Data Science, 2021.

  4. Banerjee T, Mukherjee G and Paul D. Improved Shrinkage Prediction under a Spiked Covariance Structure. Journal of Machine Learning Research, 2021, 22(180):1-40. R-Package: CASP

  5. Gangopadhyay U and Mukherjee G. Optimal Shrinkage Prediction of Several Poisson Quantiles via loss estimation submitted.

  6. Mukherjee G, Brown LD and Rusmevichientong P. Efficient Empirical Bayes prediction under check loss using Asymptotic Risk Estimates. arXiv:1511.00028 [math.ST]

Shrinkage Theory for Integrative Estimation

  1. Banerjee T, Mukherjee G and Sun W. Adaptive Sparse Estimation with Side Information. Journal of American Statistical Association, 2020. R-Package: ASUS

  2. Banerjee T and Mukherjee G. Discussion of CARS: covariate assisted ranking and screening paper by Cai, Sun and Wang. Journal of the Royal Statistical Society: Series B (Statistical Methodology) 2019.

  3. Luo J, Banerjee T, Mukherjee G and Sun W. Empirical Bayes Estimation with Side Information: A Nonparametric Integrative Tweedie Approach.Preprint, 2022.

  4. Luo J, Choi Y, Mukherjee G and Sun W. Structure adaptive sparse estimation for spatial signals: a false discovery rate thresholding approach Preprint, 2022.

Large-scale longitudinal data analysis with applications to quantitative Marketing

  1. Banerjee T, Mukherjee G, Dutta S and Ghosh P. A Large-scale Constrained Joint Modeling Approach For Predicting User Activity, Engagement And Churn With Application To Freemium Mobile Games. Journal of American Statistical Association, 2019. Matlab toolbox: click here

  2. Karmakar B, Liu P, Mukherjee G, Dutta S and Che H. Improved Retention Analysis in Freemium Role-Playing Games by Jointly Modeling Players’ Motivation, Progression and Churn. Journal of Royal Statistical Society, Series A 2022, 185:102–133.

  3. Banerjee T, Liu P, Mukherjee G, Dutta S and Che H. A Crossed Random Effects Joint Modeling Framework for Improved Prediction of Player Responses in Massively Multiplayer Online Role Playing Games. Annals of Applied Statistics, 2023.

  4. Mukhopadhay S, Kar W, Mukherjee G. Estimating Promotion Effectiveness in Email Marketing: A high-dimensional Bayesian Joint Model for Nested Imbalanced Data, Annals of Applied Statistics, 2022.

  5. Karmakar B, Kwon O, Mukherjee G, Siddharth S and Silva-Risso JM. Does a Consumer’s Previous Purchase Predict Other Consumers’ Choices? A Bayesian Probit Model with Spatial Correlation in Preference, Preprint, 2022

Two Sample testing with applications to Single-cell Virology

  1. Sen N, Mukherjee G and Arvin A. The Use of Single Cell Mass Cytometry to Define the Molecular Mechanisms of Varicella-Zoster Virus Lymphotropism. Frontiers in Microbiology, Vol 11, 2020.

  2. HIV efficiently infects T cells from the endometrium and remodels them to promote systemic viral spread. Elife, 2020; With Roan lab of UCSF.

  3. Mass Cytometric Analysis of HIV Entry, Replication, and Remodeling in Tissue CD4+ T Cells. Cell Reports, 2017, ISSN 2211-1247; With Roan lab of UCSF.

  4. Sen N, Mukherjee G and Arvin AM. Single Cell Mass Cytometry Reveals Remodeling of Human T Cell Phenotypes by Varicella Zoster Virus. Methods, 2015.

  5. Single Cell Analysis of the Remodeling of Human Tonsil T Cells by Varicella-Zoster Virus. Cell Reports, 2014; With Arvin lab of Stanford Medical School.

  6. Innate immune response to homologous rotavirus infection in the small intestinal villous epithelium at single-cell resolution. Proceedings of the National Academy of Sciences, 2012; With Greenberg lab of Stanford Medical School.

Miscelleneous

  1. The rotavirus NSP1 protein inhibits IFN-mediated STAT1 activation, Journal of Virology, 2014; With Greenberg lab of Stanford Medical School

  2. Early pregnancy testosterone after ovarian stimulation and pregnancy outcome, Fertility and Sterility, 2011 (in collaboration with Stanford Children Hospital).

  3. First Trimester Testosterone After Ovarian Stimulation and Its Effect on Pregnancy Outcomes, Fertility and Sterility, 2011 (in collaboration with Stanford Children Hospital).

  4. George EI, Marchand E, Mukherjee G, and Paul D. New and Evolving Roles of Shrinkage in Large-Scale Prediction and Inference., BIRS Workshop Report, 2019.

  5. Mukherjee G. Book review of Robust Methods for Data Reduction by A. Farcomeni and L. Greco. Journal of the American Statistical Association, 917, Vol 111, 2016.

  6. Phd Thesis: Sparsity and Shrinkage in Predictive Density Estimation Adviser: Johnstone IM. Committee: Diaconis P, Donoho DL; Stanford University, 2013.