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John Witte is an internationally recognized expert in genetic epidemiology who integrates genomic, clinical, and environmental data with machine learning to understand and predict the factors underlying cancer and complex traits. His lab and collaborators develop novel methods for risk estimation and prediction using large-scale data from biobanks and cohorts, including recent advances in genetically adjusted biomarkers to improve screening and outcome prediction, such as adjusted prostate-specific antigen levels for prostate cancer. His research program is continuously supported by the National Cancer Institute, and he has served on the Board of Scientific Counselors. As a committed educator and mentor, John has guided over 50 trainees, including pre- and postdoctoral fellows, and co-directs an NIH T32 predoctoral training program focused on the genetic and environmental basis of cancer risk. Prior to his tenure at Stanford, he held the position of Professor and Vice Chair of Epidemiology and Biostatistics at UCSF.
The Computer Science department emphasizes research potential. GRE General is currently optional but recommended for some tracks.