Speaker: Gita Sukthankar, PhD
Abstract: Data-driven social informatics unites models derived from social science with data-driven approaches in order to model and predict population behavior patterns. It can be used to advance our understanding of human behavior, guide public policy decisions, and improve user experience with social media platforms. In this talk, I'll describe work done at UCF's Intelligent Agents Lab (http://ial.eecs.ucf.edu/) in which we use a combination of agent-based modeling, machine learning, and crowdsourcing to model human social systems. The benefits of this approach will be illustrated using three case studies: 1) predicting the influence of social norms on smoking cessation behavior, 2) tracking campus parking usage using crowdsourcing and transportation modeling, 3) learning collaboration patterns from co-authorship networks. We believe that the combination of techniques yields a more nuanced view that relying on data alone.
Speaker Bio: Dr. Gita Sukthankar is an Associate Professor and Charles N. Millican Faculty Fellow in the Department of Computer Science at the University of Central Florida, and an affiliate faculty member at UCF’s Institute for Simulation and Training. She received her Ph.D. from the Robotics Institute at Carnegie Mellon and an A.B. in psychology from Princeton University. In 2009, Dr. Sukthankar was selected for the Air Force Young Investigator award, the DARPA Computer Science Study Panel, and an NSF CAREER award. Gita Sukthankar’s research focuses on multi-agent systems and computational social models. She is the lead editor of the book: Plan, Activity, and Intent Recognition: Theory and Practice and currently serves on DARPA's Information Science and Technology advisory group.
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