Lue Ping Zhao, PhD, MS

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Dr. Lue Ping Zhao PhD, MS
faculty member

Lue Ping Zhao, PhD, MS

Professor, Public Health Sciences Division, Fred Hutch

Professor
Public Health Sciences Division, Fred Hutch

Head, Genetic Epidemiology and Microarray Technology Affinity Group, Fred Hutch

Head, Genetic Epidemiology and Microarray Technology Affinity Group
Fred Hutch

Member, Translational Data Science Integrated Research Center (TDS IRC), Fred Hutch

Member
Translational Data Science Integrated Research Center (TDS IRC), Fred Hutch

Fax: 206.667.2437
Mail Stop: B3-B232

Dr. Lue Ping Zhao is a biostatistician with a background/experience in bioinformatics, epidemiology and genetics. He aims to accelerate the translation of big data technologies and findings to clinical practice and preventive medicine. Dr. Zhao studies the mechanisms of solid-tumor growth using expression and SNP arrays, and short-read sequencing methods. His research interests include genetic epidemiology, biomedical informatics, population-based study designs and risk-prediction modeling. He develops statistical methods for assessing the interplay of genetics and environment on disease risk, including genome-wide association studies and gene-sequence analysis. He has developed innovative study designs and methods that enable interdisciplinary collaborations, bridging the gap between genetic and epidemiologic research.

Other Appointments & Affiliations

Affiliate Investigator, Clinical Research Division, Fred Hutch

Affiliate Investigator
Clinical Research Division, Fred Hutch

Education

PhD, Biostatistics, University of Washington, 1989

MS, Biostatistics, University of Washington, 1987

MS, Statistics in Health Science, Shanghai Medical University, 1985

BS, Computer Science, Shanghai University of Science and Technology, 1982

Research Interests

Estimating equation techniques, developing statistical methods for assessing genetic associations, gene-environment interactions including methods for haplotype-based methods, genome-wide association studies, time-varying phenotypes and sequence analysis.