Latest:

Predicting cervical cancer DNA methylation from genetic data using multivariate classified mixed model prediction

H. Zhang, X. Chen, R. Balise, J. Jiang, N. Ayad and J.S. Rao
Canadian Journal of Statistics (to appear)
Black and white portrait of J. Sunil Rao

J. Sunil Rao's interests are in applied statistics, biostatistics, small area estimation and machine learning. His current research focuses on cancer, health disparities and opioid relapse. He has also developed software packages with various students and collaborators.

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Research Interests:

High throughput cancer genomic data modeling;
Health disparity estimation;
Opioid relapse prediction;
Machine learning;
High dimensional modeling; Bayesian model selection; Mixed model selection
and prediction;
Small area estimation; Bump/mode hunting;
Robust estimation;
Precision medicine;
Modeling of
pharmacogenomic data

Books

Available August, 2025

Robust Small Area Estimation: Methods, Theory, Applications and Open Problems

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Highlighted

Software Sites

PRIMsrc

Implements a unified treatment of the “Bump Hunting” task in high-dimensional space.
MOst Recent

Publications and Articles

Lenses of variation

T.Liu, D. Diaz-Pachon and J.S. Rao

Statistical learning does not always entail knowledge

D.A. Pachon, R. Gallegos, O. Hossjer and J.S. Rao
Publication

V.K. Gupta Endowment Award Lecture 2024: Modernizing linear mixed model prediction

J.S. Rao
Statistics and Applications (to appear)
LINK
J. Sunil Rao, Ph.D.

Professor, Division of Biostatistics
School of Public Health
Director of Biostatistics, Masonic Cancer Center
University of Minnesota, Twin Cities


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