Adam Yala

My interests lie in the intersection of Machine Learning and Precision Medicine. I believe that algorithmic innovation can create more precise and equitable healthcare. Towards this goal, my research focuses on designing modeling approaches that are robust to data-generation biases, offer safe-guards for clinical deployment and can adapt to diverse clinical requirements. My previous work has contributed to three areas: 1) predicting future cancer risk, 2) designing personalized screening policies and 3) private data sharing through neural obfuscation. My tools are implemented at multiple hospital systems around the world, and underlie prospective clinical trials. The ultimate goal of these efforts is to change the standard of care.