***Overflow seating available in 4403 Siebel Center***
Abstract: I will share directions and results enabled by the confluence of large-scale data resources, jumps in computational power, and advances in machine intelligence. I will focus on efforts that leverage learning and inference to help people with decisions, touching on work in transportation, medicine, human-machine collaboration. I will present projects that center on using traditional sources of data, such as GPS data and electronic health records, and efforts that harness more exotic streams of information, including the use of planes in flight as a large-scale sensor network. I will conclude by discussing the promise of leveraging data, learning, and reasoning to enable new kinds of collaboration between people and machines to address challenges in science, society, and daily life.
Bio: Eric Horvitz is a technical fellow at Microsoft and director of the Microsoft Research lab at Redmond. He has pursued principles and applications of artificial intelligence, with contributions in decisions under uncertainty, machine learning, bounded rationality, information retrieval and human computation. His research and collaborations have led to fielded systems in healthcare, transportation, human-computer interaction, online services, robotics, and operating systems. He has received the Feigenbaum Prize and the ACM-AAAI Allen Newell Award for his research contributions. He has been elected fellow of the NAE, AAAI, ACM, and AAAS and he has been inducted into the CHI Academy. He was president of the AAAI and chair of the AAAS Section on Computing, and has served on DARPA’s Information and Technology Study Group (ISAT), the NSF CISE Advisory Committee, the Computing Community Consortium (CCC), and the Computer Science and Telecommunications Board (CSTB). More information can be found at http://research.microsoft.com/~horvitz.