John Guttag






John Guttag is the Dugald C. Jackson Professor of Computer Science and Electrical Engineering at MIT. He leads MIT’s Computer Science and Artificial Intelligence Laboratory’s Clinical and Applied Machine Group. The group develops and applies advanced machine learning and computer vision techniques to a variety of clinically relevant problems. Current research projects include prediction and reduction of adverse medical events, matching patients to therapies and providers, and medical imaging. He has published this research in  machine learning, general AI, and computer vision venues—as well as in medically-oriented conferences and journals. 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. His former students have risen to positions of prominence and made important contributions to academia, industry, and government.

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 online courses on this topic have been taken by over two million students.

In addition to his academic activities, Professor Guttag has extensive industrial experience.  He has served on the board of directors of three public and three private companies.  He is presently Chief Scientific Officer and a founder of Health[at]Scale Technologies. The company’s machine intelligence platform for care prediction is used by payers and providers to help manage care for tens of millions of patients.

Professor Guttag is a Fellow of the ACM and a member of the American Academy of Arts and Sciences.

Impact Areas


 1 More


Community of Research

Systems Community of Research

The Systems CoR is focused on building and investigating large-scale software systems that power modern computers, phones, data centers, and networks, including operating systems, the Internet, wireless networks, databases, and other software infrastructure.