Gerald Tesauro is a Principal Research Staff Member in Cognitive Computing at IBM's TJ Watson Research Center. He is best known for developing TD-Gammon, a self-teaching neural network that learned to play backgammon at human world championship level, and for developing advanced methods for game strategy decisions in Watson, IBM's Jeopardy! supercomputer. He has also worked on theoretical and applied machine learning in a wide variety of other settings, including multi-agent learning, dimensionality reduction, computer virus recognition, computer chess (Deep Blue), intelligent e-commerce agents and autonomic computing. Dr. Tesauro has been extensively involved in organizing AI-related conferences and workshops. Most notably, he has served as Program Chair, General Chair, Workshops Chair, and Tutorials Chair of NIPS (Neural Information Processing Systems), in addition to many years of service on the NIPS Organizing Committee. Dr. Tesauro is a Fellow of the AAAI, a Senior Member of the IEEE, a member of the NIPS Foundation Board of Directors, and an Associate Editor of the ICGA (Intl. Computer Games Assn.) Journal.