Latest:

How to apply Bayesian variable selection with multiply imputed data

S. Bainter, Z. Mao and J.S. Rao
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

CHAPMAN AND HALL/CRC BIOSTATISTICS SERIES

Statistical Methods for Health Disparity Research

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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

Learning, knowledge, maximum entropy, and maximum likelihood

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
Article

Mixed model selection with applications to small area estimation

J.S. Rao and J.N.K. Rao
Statistics and Applications, Special Issue In Memory of Prof. C.R. Rao (to appear)
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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