John Guttag is the Dugald C. Jackson Professor of Computer Science and Electrical Engineering at MIT. He leads the Computer Science and Artificial Intelligence Laboratory’s Data Driven Inference Group. The group uses advanced machine learning and computer vision to improve outcomes in medicine, finance, and sports. Current research projects include prediction and reduction of adverse medical events, matching patients to therapies and providers, and medical imaging. Professor Guttag has also done research, published, and lectured in the areas of sports analytics, financial analytics, software defined radios, software engineering, mechanical theorem proving, and hardware verification.
From January of 1999 through August of 2004, Professor Guttag served as Head of MIT’s Electrical Engineering and Computer Science Department. He served as Associate Department Head from Computer Science from 1993 to 1998.
In recent years, Professor Guttag's classroom teaching has centered around helping students learn to apply computational modes of thought to frame problems and to guide the process of extracting useful information from data. His textbook on this topic, Introduction to Computation and Programming Using Python, with Application to Understanding Data, is used in online courses that have been taken by over a million students.
In addition to his academic activities, Professor Guttag has extensive industrial experience. He is currently Chairman of the Board of Directors and Chief Scientist of HEALTH[at]SCALE Technologies and on the Board of Directors of Frontiir.
Professor Guttag received a bachelor's degree in English from Brown University in 1971, and a master's degree in applied mathematics from Brown in 1972. In 1975, he received a doctorate in computer science from the University of Toronto. He was a member of the faculty at the University of Southern California from 1975-1978, and joined the MIT faculty in 1979.
Professor Guttag is a Fellow of the ACM and a member of the American Academy of Arts and Sciences.