Adam Yala is an assistant professor in Computational Precision Health, Statistics, and Computer Science (EECS) and a research affiliate of the MIT Jameel Clinic. His lab develops machine learning methods for personalized cancer care and to translate them to clinical practice; his overarching goal is to offer each patient the right intervention (e.g. screening exam or particular treatment choice) at the right time according to their individual risks and preferences. To this end, the Yala lab focuses on three major themes: 1) modeling full patient records (e.g. multi-modal imaging, pathology, etc) to better predict patient outcomes, 2) deriving better decisions from AI-driven predictors (e.g. screening and treatment policies, choosing therapeutic targets, providing decision quality guarantees, etc.) and 3) clinical translation. His tools are implemented at multiple hospital systems around the world, and underlie prospective clinical trials.
Eppy Award: Investigative Reporting 2022
Falling Walls Finalist: Life Science 2022
Best Paper Award, EMNLP 2016
NSF Fellowship 2016
MIT EECS Fellowship 2016