On Networks and Behavior: Strategic Inference and Machine Learning
Stony Brook University
Tuesday, December 16, 2014|
4:00pm - 5:30pm
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About the Event
Studying complex behavior in economic, social, or other similar systems is an important scientific endeavor with potentially direct impact to society via the eventual commercialization of relevant technology. The big-data revolution offers the opportunity to easily collect and process large amounts of data recording system behavior. Yet, our fundamental understanding of real-world complex systems remains slim at best.
Luis E. Ortiz is an assistant professor at Stony Brook University. Prior to joining Stony Brook, he was an assistant professor at the University of Puerto Rico, Mayagüez; a postdoctoral lecturer at MIT; a postdoctoral researcher at the University of Pennsylvania; and a consultant in the field of AI and ML at AT&T Labortories-Research. He received an Sc.M. degree and a PhD degree in computer science in 1998 and 2001, respectively, both from Brown University. He received a BS degree in computer science in 1995 from the University of Minnesota. His main research areas are AI and ML. His current focus is on computational game theory and economics, with applications to the study of influence in strategic, networked, large-population settings, and learning game-theoretic models from data on strategic behavior. Other interests include, game-theoretic models for interdependent security, algorithms for computing equilibria in games, connections to probabilistic graphical models, and AdaBoost. Prof. Ortiz received the NSF CAREER award in 2011. He was a National Physical Science Consortium (NPSC) Ph.D. Fellow and an NSF Minority Graduate Fellow.
Open to: Public