Peter Szolovits

Peter Szolovits is a Professor of Computer Science and Engineering at MIT's Department of Electrical Engineering and Computer Science (EECS), leading the Clinical Decision-Making Group in CSAIL. He holds affiliate roles at the MIT Institute for Medical Engineering and Science (IMES) and Harvard/MIT Health Sciences and Technology (HST). His research integrates AI methods with healthcare challenges, focusing on decision support systems, natural language processing (NLP) of clinical narratives, and privacy-preserving health information systems.

Education: B.S. in Physics and Ph.D. in Information Science from Caltech. Awards include membership in the National Academy of Medicine, and fellowships from AAAI, ACMI, and other leading organizations.

Key projects include developing CliNER (clinical NLP tool), predicting ICU interventions via machine learning, and analyzing racial disparities in end-of-life care. He teaches courses on biomedical computing, AI, and medical decision-making systems.

His work bridges computational methods with clinical practice, emphasizing explainable AI and ethical healthcare applications. Current research explores automated phenotyping, EHR pre-training benchmarks, and mitigating biases in AI-driven healthcare.