Four EECS faculty members are named as world leaders in AI for health

Professors Barzilay, Jaakkola, Kellis, and Szolovits are among 100 leaders recognized by a top technology think tank.

CSAIL and EECS Staff

Four EECS professors are among the top 100 global leaders in artificial intelligence (AI) for health, according to a recent report developed by a top technology think-tank.

Deep Knowledge Analytics’s “Top 100 AI Leaders in Drug Discovery and Advanced Healthcare” (PDF) looked at scientists, clinicians and technologists across academia, pharmaceutical, and AI companies. Among the honorees were EECS professors Regina Barzilay, Tommi Jaakkola, Manolis Kellis, and Peter Szolovits. All are also principal investigators in CSAIL.

Barzilay, the Delta Electronics Professor of Electrical Engineering and Computer Science, co-leads MIT CSAIL’s Natural Language Processing Group. Her research interests are in natural language processing, applications of deep learning to chemistry and oncology. Working with Massachusetts General Hospital, she is developing algorithms that can learn to improve models of disease progression, prevent overtreatment, and detect cancer earlier and more accurately. Her awards include a MacArthur Foundation Fellowship, an National Science Foundation (NSF) CAREER Award, and a Microsoft Fellowship, and she is a fellow of the of the American Association for Artificial Intelligence (AAAI).

Jaakkola is the inaugural Thomas Siebel Professor in EECS and in the Institute for Data, Systems, and Society (IDSS). He co-leads the Natural Language Processing Group with Barzilay. His research interests include many aspects of machine learning, statistical inference and estimation, and analysis and development of algorithms for various modern estimation problems such as those involving predominantly incomplete data sources. His applied research focuses on problems in natural language processing, computational chemistry, as well as computational functional genomics.. He has held editorial positions on prestigious journals such as the Journal of Machine Learning Research and the Journal of Artificial Intelligence Research, and has co-chaired or overseen areas of numerous major conferences.

Kellis, a professor of computer science, directs MIT’s Computational Biology Group. He is also a member of the Broad Institute of MIT and Harvard. His research spans disease genetics, epigenomics, gene circuitry, and comparative genomics, and he has helped direct several large-scale genomics projects, including Roadmap Epigenomics, ENCODE, and Genotype Tissue-Expression (GTEx) project. He received the U.S. Presidential Early Career Award in Science and Engineering (PECASE) from then-President Barack Obama, and has also received an Alfred P. Sloan Foundation Award and an NSF CAREER Award, among others.

Szolovits, professor of computer science and engineering, heads up CSAIL’s Clinical Decision-Making Group. He is also an associate member of the MIT Institute for Medical Engineering and Science (IMES) and on the faculty of the Harvard/MIT Health Sciences and Technology program. His research centers on the application of AI methods to problems of medical decision making, predictive modeling, and system design for healthcare institutions. He has worked on problems of diagnosis, therapy planning and medical monitoring, computational aspects of genetic counseling, controlled sharing of health information, and privacy and confidentiality issues in medical record systems. Among other honors, he is a member of the National Academy of Medicine and an AAAI fellow.

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