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Adam Yala, PhD

Adam Yala, PhD

Assistant Professor of Computational Precision Health, EECS at UC Berkeley and UCSF

Adam Yala is an Assistant Professor of Computational Precision Health and EECS at UC Berkeley and UCSF. His research focuses on developing machine learning methods for personalized medicine and translating them to clinical care. His previous research has contributed to areas of: 1) predicting future cancer risk, 2) designing personalized screening policies. Adam's tools underly multiple prospective trails and his research has been featured in the Washington Post, New York Times, Boston Globe and Wired. Prof Yala obtained his BS, MEng and PhD in Computer Science from MIT and he was a member of MIT Jameel Clinic and MIT CSAIL.

Research Overview:

Machine Learning for Precision Oncology: Algorithms for Multi-modal Inference and Policy Design
The Yala lab develops machine learning models for personalized care and translates them to clinical practice. It focuses on designing modeling approaches that are robust to data-generation biases, offer mechanisms for clinical deployment and can adapt to diverse clinical requirements.

Computational health science interests: