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Publications

Preprints

  • Lee, S., Mukherjee, R., Mukherjee, S (2025). Inference on Gaussian mixture models with dependent labels. arXiv preprint [link]

  • Chen, X., Liu, L., Mukherjee, R. (2025). Method-of-Moments Inference for GLMs and Doubly Robust Functionals under Proportional Asymptotics. arXiv preprint [link]

  • McGrath, S., Mukherjee, R. (2025). Nuisance Function Tuning and Sample Splitting for Optimal Doubly Robust Estimation. arXiv preprint [link]

  • Bhattacharya, S., Dey, R., Mukherjee, R. (2024). PC Adjusted Testing for Low-Dimensional Parameters. arXiv preprint [link]

  • Mukherjee, R., Sen, S. (2020). On Minimax Exponents of Sparse Testing. arXiv preprint [link]

2025

  • Levis, A., Mukherjee, R., Wang, R., & Haneuse, S. (2025). Robust causal inference for point exposures with missing confounders. Canadian Journal of Statistics, 53(2), e11832.

  • Jiang, K., Mukherjee, R., Sen, S., & Sur, P. (2025). A New Central Limit Theorem for the Augmented IPW Estimator: Variance Inflation, Cross-Fit Covariance, and Beyond. The Annals of Statistics, 53(2), 647–675.

  • Sun, S., Haneuse, S., Levis, A., Lee, C., Arterburn, D., Fischer, H., Shortreed, S.M., & Mukherjee, R. (2025). Estimating weighted quantile treatment effects with missing outcome data by double sampling. Biometrics, 81(2), ujaf038.

  • Bhattacharya, S., Mukherjee, R., & Ray, G. (2025). Sharp Signal Detection Under Ferromagnetic Ising Models. IEEE Transactions on Information Theory.

  • Bhattacharya, S., Mukherjee, R., & Ogburn, B. (2025). Nonsense associations in Markov random fields with pairwise dependence. Biometrika, asaf041.

  • McGrath, S., Mukherjee, D., Mukherjee, R., & Wang, Z. (2025). Optimal Nuisance Function Tuning for Doubly Robust Functional Estimation under Proportional Asymptotics. NeurIPS (Spotlight).

  • Mukherjee, R. (2025). From Univariate Analysis to Global Inference. Harvard Data Science Review.

  • Wu, B., Vyas, C., Medina, A., Slopen, N., Mahalingaiah, S., Chavarro, J., Mukherjee, R., Weisskopf, M., & Roberts, A. (2025). Estimating the associations between women's maltreatment in childhood and inflammatory biomarker levels prior to and during pregnancy. PLOS One.

  • Tang, I., Knekt, P., Rantakokko, P., Heliövaara, M., Rissanen, H., Ruokojärvi, P., Mukherjee, R., & Weisskopf, M. (2025). Pre-disease biomarkers of persistent organic pollutants (POPs) and amyotrophic lateral sclerosis (ALS) risk in Finland. Environmental Health Perspectives.

2024

  • Benz, L., Mukherjee, R., Wang, R., Arterburn, D., Fischer, H., Lee, C., Shortreed, S.M., & Haneuse, S. (2024). Adjusting for Selection Bias Due to Missing Eligibility Criteria in Emulated Target Trials. American Journal of Epidemiology, kwae471.

  • Levis, A., Mukherjee, R., Wang, R., & Haneuse, S. (2024). Double sampling and semiparametric methods for informatively missing data. Statistics in Medicine, 43(30), 6086–6098.

  • Deb, N., Mukherjee, R., Mukherjee, S., & Yuan, M. (2024). Detecting Structured Signals in Ising Models. The Annals of Applied Probability, 34(1A), 1–45.

  • Laha, N., Sonabend, A., Mukherjee, R., & Cai, T. (2024). Finding the Optimal Dynamic Treatment Regime under Fisher Consistent Surrogate Loss. The Annals of Statistics, 52(2), 679–707.

  • Liu, L., Mukherjee, R., & Robins, J. (2024). Assumption-lean falsification tests of rate double-robustness of double-machine-learning estimators. Journal of Econometrics, 240(2), 105500.

  • Farmer, J., Specht, A., Pushon, T., Jackson, B., Bidlack, F., Bakalar, C., Mukherjee, R., Davis, M., Steadman, D., & Weisskopf, M. (2024). Lead exposure across the life course and age of death. Science of The Total Environment, 927, 171975.

  • Bhattacharya, B., & Mukherjee, R. (2024). Sparse Uniformity Testing. IEEE Transactions on Information Theory.

2023

  • Chhor, J., Mukherjee, R., & Sen, S. (2023). Sparse Signal Detection in Heteroscedastic Gaussian Sequence Models: Sharp Minimax Rates. Bernoulli, 30(3), 2127–2153.

  • Sonabend, A., Laha, N., Cai, T., & Mukherjee, R. (2023). Semi-Supervised Off Policy non-Markovian Reinforcement Learning. Journal of Machine Learning Research, 24(323), 1–86.

  • McGrath, S., Mukherjee, R., Requia, W. J., & Lee, W. L. (2023). Wildfire exposure and academic performance in Brazil: a causal inference approach for spatiotemporal data. Science of The Total Environment, 905, 167625.

  • Laha, N., Huey, N., Coull, B., & Mukherjee, R. (2023). On Statistical Inference with High Dimensional Sparse CCA. Information and Inference, 12(4), 2818–2850.

  • Hou, J., Mukherjee, R., & Cai, T. (2023). Efficient and Robust Semi-supervised Estimation of ATE with Partially Annotated Treatment and Response. Journal of Machine Learning Research, 24(265), 1–58.

2022

  • Ho, C.-H., Huang, Y.-J., Lai, Y.-J., Mukherjee, R., & Hsiao, C.-H. (2022). The misuse of distributional assumptions in functional class scoring gene-set and pathway analysis. G3: Genes|Genomes|Genetics, 12(1), jkab365.

  • Huang, Y.-J., Mukherjee, R., & Hsiao, C.-H. (2022). Probabilistic Edge Inference of Gene Networks with Bayesian Markov Random Field Modeling. Frontiers in Genetics, 13, 1034946.

  • Deng, W., Cocker, B., Mukherjee, R., Liu, J., & Coull, B. (2022). Towards a Unified Framework for Uncertainty-aware Nonlinear Variable Selection with Theoretical Guarantees. NeurIPS, 35, 27636–27651.

  • Laha, N., & Mukherjee, R. (2022). On Support Recovery With Sparse CCA: Information Theoretic and Computational Limits. IEEE Transactions on Information Theory, 69(3), 1695–1738.

  • Khorasanizadeh, M., Maroufi, S. F., Mukherjee, R., Sankaranarayanan, M., & Moore, J. (2022). Middle Meningeal Artery Embolization in Adjunction to Surgical Evacuation for Treatment of Subdural Hematomas: a Nationwide Comparison of Outcomes with Isolated Surgical Evacuation. Neurosurgery, 10–1227.

2021

  • Mukherjee, R., & Sen, S. (2021). Testing Degree Corrections in Stochastic Block Models. Annales de l'Institut Henri Poincaré, Probabilités et Statistiques, 57(3), 1583–1635.

  • Mukherjee, R., & Ray, G. (2021). On Testing for Parameters in Ising Models. Annales de l'Institut Henri Poincaré, Probabilités et Statistiques, 58(1), 164–187.

  • Liu, R., Mukherjee, R., & Robins, J. (2021). On Adaptive Estimation of Nonparametric Functionals. Journal of Machine Learning Research, 22(1), 4507–4572.

  • Requia, W. J., Amini, H., Mukherjee, R., Gold, D., & Schwartz, J. (2021). Health impacts of wildfire-related air pollution in Brazil: A nationwide study of more than 2 million hospital admissions between 2008 and 2018. Nature Communications, 12(1), 6555.

  • Requia, W. J., Papatheodorou, S., Koutrakis, P., Mukherjee, R., & Roig, H. L. (2021). Increased preterm birth following maternal wildfire smoke exposure in Brazil. International Journal of Hygiene and Environmental Health, 240, 113901.

2020

  • Lin, L., Mukherjee, R., & Robins, J. M. (2020). On nearly assumption-free tests of nominal confidence interval coverage for causal parameters estimated by machine learning. Statistical Science, 35(3), 518–539.

  • Lin, L., Mukherjee, R., & Robins, J. M. (2020). Rejoinder to "On nearly assumption-free tests of nominal confidence interval coverage for causal parameters estimated by machine learning." Statistical Science, 35(3), 518–539.

  • Han, Y., Jiao, J., & Mukherjee, R. (2020). On estimation of ℓp-norms in Gaussian white noise models. Probability Theory and Related Fields, 177, 1243–1294.

2019

  • Mukherjee, R., & Sen, B. (2019). On Efficiency of Plug-In Principles for Estimating Smooth Integral Functionals of a Non-increasing Density. Electronic Journal of Statistics, 13(2), 4416–4448.

2018

  • Mukherjee, R., Mukherjee, S., & Sen, S. (2018). Detection Thresholds for the β-Model on Sparse Graphs. The Annals of Statistics, 46(3), 1288–1317.

  • Mukherjee, R., Mukherjee, S., & Yuan, M. (2018). Global Testing against Sparse Alternatives under Ising Models. The Annals of Statistics, 46(5), 2062–2093.

2017

  • Barnett, I., Mukherjee, R., & Lin, X. (2017). Generalized Higher Criticism for SNP sets in Genetic Association Testing. Journal of the American Statistical Association, 112(517), 64–76.

  • Basu, K., & Mukherjee, R. (2017). Asymptotic Normality of Scrambled Geometric Net Quadrature. The Annals of Statistics, 45(4), 1759–1788.

  • Robins, J. M., Li, L., Mukherjee, R., Tchetgen Tchetgen, E., & van der Vaart, A. (2017). Minimax Estimation of a Functional in a Structured High Dimensional Model. The Annals of Statistics, 45(5), 1951–1987.

  • Mukherjee, R., & Sen, S. (2017). Optimal Adaptive Inference in Random Design Binary Regression. Bernoulli, 24(1), 699–739.

2015

  • Mukherjee, R., Pillai, N., & Lin, X. (2015). Hypothesis Testing for High-Dimensional Sparse Binary Regression. The Annals of Statistics, 43(1), 352–381.