Tom Mitchell

Digital Fellows • Seminar Speakers
I believe this is the decade when AI can change education for the better… The opportunity is great, but we need to organize and fund this research if we want to turn this potential into reality.

Digital Fellow, Stanford Digital Economy Lab | Founders University Professor, Carnegie Mellon University

Contact
tommitchell@cmu.edu
Personal Website

Tom M. Mitchell is the Founders University Professor at Carnegie Mellon University, where he founded the world’s first Machine Learning Department, and served as Interim Dean of the School of Computer Science (2018-2019). He is also a Digital Fellow at the Stanford Digital Economy Lab.

He has worked on machine learning and AI ever since his 1979 Stanford Ph.D., and he remains optimistic about its future. In 2010 Mitchell was elected to the U.S. National Academy of Engineering “For pioneering contributions and leadership in the methods and applications of machine learning.”

Tom Mitchell is interested in many areas of computer science, but especially in how to construct computers that learn from experience.  At the heart of the problem of machine learning is the question of how to automatically formulate general hypotheses given a collection of very specific training examples.

His research has addressed a number of approaches to this question, including statistical approaches that find regularities over large numbers of training examples, and analytical approaches that generalize from very few examples and rely instead on prior knowledge and reasoning.

Machine Learning: How Did We Get Here? is a series of interviews with the pioneers of machine learning. Through the personal stories of the people who built the field, the podcast goes beyond lessons about the technology to highlight the passion, curiosity, and humanity behind it.

Check out the podcast →