100 Union St SE
Minneapolis, MN 55455
My research focuses on the development and validation of clinical prediction models for risk stratification and treatment planning in genitourinary cancer, especially renal cell carcinoma. In particular, I'm interested in the use of deep learning to incorporate tumor appearance into prediction models in more expressive and objective ways while maintaining transparency and biological plausibility. I serve as the lead organizer for the biennial Kidney Tumor Segmentation Challenge (KiTS), and the annual MICCAI LABELS workshop, which focuses on the science of creating medical imaging datasets for machine learning.
I received my B.S. in Computer Science from the University of Minnesota in the Spring of 2017.