Ryan Adams is assistant professor of computer science in the School of Engineering and Applied Sciences at Harvard University. Adams’ research is primarily in the area of machine learning, the subfield of computer science that is concerned with the development of algorithms which can adapt to experience. Adams leads the Harvard Intelligent Probabilistic Systems group, which focuses on probabilistic approaches to building such algorithms, working at the interface of computer science, statistics and computational neuroscience. In broad terms, he is interested in understanding the computation that lies beneath intelligence and developing artificial systems that can discover complex structure in data. Adams completed his Ph.D. in physics under David MacKay at the University of Cambridge, where he was a Gates Cambridge Scholar and a member of St. John’s College. His doctoral work won the honorable mention for the Savage Award from the International Society for Bayesian Analysis. Before coming to Harvard, Adams spent two years as a junior research fellow at the University of Toronto as a part of the Canadian Institute for Advanced Research. Adams has won awards for his work at several major international conferences such as the International Conference on Machine Learning, the International Conference on Artificial Intelligence and Statistics, and the Conference on Uncertainty in Artificial Intelligence. Adams is also the recipient of a Defense Advanced Research Projects Agency Young Faculty Award.
Past Project: Decoding internal state to predict behavior