Adjunct Professor, Carnegie Mellon University, Microsoft Research
Dr. Gordon is the Research Director for the Microsoft Research Montréal lab, and a Professor in the Machine Learning Department at Carnegie Mellon University. He has also served as Interim Department Head and as Associate Department Head for Education for the Machine Learning Department. Dr. Gordon’s research has focused on artificially-intelligent systems that are capable of long-term thinking such as reasoning ahead to solve a problem, planning a sequence of actions or inferring unseen properties from observations. Particularly, he looks at how to combine machine learning with these long-term thinking tasks. Dr. Gordon received his B.A. in Computer Science from Cornell University in 1991, and his PhD in Computer Science from Carnegie Mellon University in 1999. His research interests include artificial intelligence, statistical machine learning, educational data, game theory, multi-robot systems, and planning in probabilistic, adversarial, and general-sum domains. His previous appointments include Visiting Professor at the Stanford Computer Science Department and Principal Scientist at Burning Glass Technologies in San Diego.
Decomposed Mutual Information Estimation for Contrastive Representation Learning
Alessandro Sordoni, Nouha Dziri, Hannes Schulz, Geoff Gordon, Philip Bachman and Remi Tachet des Combes