Bhramar Mukherjee

Bhramar Mukherjee adalah seorang biostatistikawan, ilmuwan data, profesor dan peneliti India-Amerika. Ia adalah John D. Kalbfleisch Collegiate Professor and the Chair of Department of Biostatistics, seorang profesor epidemiologi di Universitas Michigan. Ia menjabat sebagai wakil direktur Ilmu Data Kuantitatif di University of Michigan Rogel Cancer Center. Ia terpilih menjadi Ketua Committee of Presidents of Statistical Societies (COPSS) untuk masa jabatan tiga tahun sejak 2019.

Bhramar Mukherjee
Lahir	22 Oktober 1973 Kolkata, India
Kebangsaan	India-Amerika
Kewarganegaraan	Amerika Serikat
Pekerjaan	Biostatistikawan, ilmuwan data, profesor dan peneliti.
Gelar	John D Kalbfleisch Collegiate professor and Chair of Biostatistics.
Latar belakang akademis
Alma mater	Presidency College (BSc) Indian Statistical Institute (M.Stat) Purdue University (MS, PhD)
Tesis	Optimal designs for estimating the path of a stochastic process. (2001)
Pembimbing doktoral	William J. Studden
Karya akademis
Lembaga	Universitas Michigan
Penghargaan (2017) Fellow of the American Association for the Advancement of Science (en) (2012) Fellow of the American Statistical Association (en)

Artikel terpilih

• Sinha S, Mukherjee B, Ghosh M, Mallick BK, and Raymond JC. Bayesian semi-parametric analysis of matched case-control studies with missing exposure. Journal of the American Statistical Association, 100:591-601, 2005.
• Mukherjee B and Chatterjee N. Exploiting gene-environment independence for analysis of case-control studies: An empirical-Bayes type shrinkage estimator to trade off between bias and efficiency. Biometrics, 64(3):685-94, 2008, PMID 18162111.
• Kastrinos F, Mukherjee B, Tayob N, Sparr J, Raymond VM, Wang F, Bandipalliam P, Stoffel EM, Gruber SB, Syngal S. The Risk of Pancreatic Cancer in Lynch Syndrome. Journal of the American Medical Association, 302(16):1790–95, 2009, PMCID: PMC4091624.
• Mukherjee B, Ahn J, Gruber SB, and Chatterjee N. Testing gene-environment interaction in large-scale association studies: possible choices and comparison. American Journal of Epidemiology, 175(3):177-90, 2012, PMCID: PMC3286201. Discussion paper with invited commentary.
• Mukherjee B, DeLancey JO, Raskin L, et al. Risk of Non-Melanoma Cancers in CDKN2A Mutation Carriers. The Journal of the National Cancer Institute, 104(12):953-56, 2012, PMCID: PMC3379723.
• Sun Z, Tao Y, Li S, Ferguson KK, Meeker JD, Park SK, Batterman SA, Mukherjee B. Statistical strategies for constructing health risk models with multiple pollutants and their interactions: possible choices and comparison. Environmental Health, 12(1):85, 2013, PMCID: PMC3857674.
• Boonstra PS, Mukherjee B and Taylor JMG. Bayesian shrinkage methods for partially observed high-dimensional data. The Annals of Applied Statistics, 7(4):2272–92, 2013, PMCID: PMC3891514.
• He Z, Zhang M, Lee S, Smith JA, Guo X, Palmas W, Kardia SLR, Diez-Roux AV, Mukherjee B. Multi-marker tests for joint association in longitudinal studies using the genetic random field model. Biometrics, 71(3):606-15, 2015, PMCID: PMC4601568.
• He Z, Zhang M, Lee S, Smith JA, Kardia SLR, Diez Roux AVD, Mukherjee B, Set-Based Tests for Gene-Environment Interaction in Longitudinal Studies. The Journal of the American Statistical Association, Application and Case Studies, 112(519):966-978, 2017, PMCID: PMC5954413.
• Fritsche L, Gruber SB, Wu Z, Schmidt EM, Zawistowski M, Moser SE, Blanc V, Brummet C, Kheterpal S, Abecasis GA, Mukherjee B. Association of Polygenic Risk Scores for Multiple Cancers in a Phenomewide Study: Results from The Michigan Genomics Initiative, The American Journal of Human Genetics, 102:1048–1061, 2018, PMCID: PMC5992124.
• Beesley LJ, Mukherjee B. Statistical inference for association studies using electronic health records: handling both selection bias and outcome misclassification. Biometrics, 1-20,2020, PMID 33179768.
• Ray D, Salvatore M, Bhattacharyya R, ...,Ghosh P. Mukherjee, B. Predictions, role of interventions and effects of a historic national lockdown in India's response to the COVID-19 pandemic: data science call to arms. Harvard Data Sci Rev. 2020;2020(Suppl 1), PMCID: PMC7326342.