Tim Randolph

Tim Randolph is a Professor in the Biostatistics Program of the Public Health Sciences Division at Fred Hutchinson Cancer Center, with dual appointments in the Clinical Research Division and as a Member of the Translational Data Science Integrated Research Center. He also serves as an Affiliate Investigator in the Translational Science and Therapeutics Division.

Education:

• PhD in Mathematics from the University of Oregon (1990)
• BS in Mathematics from the University of Puget Sound (1982)

Dr. Randolph specializes in developing statistical and machine learning methodologies for analyzing complex molecular datasets including gene expression, metabolites, microbiome compositions, and neuro-connectivity patterns. His research integrates multi-omic data to uncover relationships between molecular measurements and health outcomes, with emphasis on cancer detection, subtype classification, and treatment response. Key methodological innovations include Kernel Penalized Regression, Generalized Matrix Decomposition, and tissue image analysis frameworks like TACOMA and mIHC-LAND.

The Randolph Lab collaborates extensively with clinical and public health scientists across Fred Hutch, focusing on translational applications in lung cancer (through the Lung SPORE program), HIV research, and microbiome-cancer interactions. Current projects address longitudinal HIV data analysis, multiplex immunohistochemistry quantification, and integrative modeling of metabolite-bacteria interactions in disease contexts.