Peter Szolovits

Peter Szolovits is Professor (Post-Tenure) of Computer Science and Engineering in the MIT Department of Electrical Engineering and Computer Science (EECS) and in the Harvard/MIT Health Sciences and Technology (HST) program. He heads the Clinical Decision-Making Group within the MIT Computer Science and Artificial Intelligence Laboratory (CSAIL).

His research centers on the application of AI methods to problems of medical decision making,natural language processing to extract meaningful data from clinical narratives to support translational medicine, and the design of information systems for health care institutions and patients. He has worked on problems of diagnosis, therapy planning, execution and monitoring for various medical conditions, computational aspects of genetic counseling, controlled sharing of health information, and privacy and confidentiality issues in medical record systems. His interests in AI include knowledge representation, qualitative reasoning, and probabilistic inference.

His interests in medical computing include Web-based heterogeneous medical record systems, life-long personal health information systems, and design of cryptographic schemes for health identifiers. He teaches classes in artificial intelligence, machine learning, programming languages, medical computing, medical decision making, knowledge-based systems and probabilistic inference.

His physics bachelor's degree and his PhD in information science are both from Caltech. Prof. Szolovits was elected to the National Academy of Medicine and to Fellowships in the American Association for Artificial Intelligence, the American College of Medical Informatics, the American Institute for Medical and Biological Engineering, and the International Academy of Health Sciences Informatics. He has served as a member of the National Research Council's Computer Science and Telecommunications Board and as a member of the National Library of Medicine’s Biomedical Library and Informatics Review Committee. He was the 2013 recipient of the Morris F. Collen Award of Excellence from the American College of Medical Informatics.