Haifeng
Xu,
PhD
candidate
Computer
Science
Department,
University
of
Southern
California
Strategic interactions among self-interested agents (a.k.a., games) are ubiquitous, ranging from economic activity in daily life and the Internet to defender-adversary interactions in national security. A key variable influencing agents' strategic decision making is the information they have available about their environment as well as the preferences and actions of others.
In this talk, I will describe my work on computational questions pertaining to the role of information in games. In particular, I will illustrate the double-edged role of information through two threads of my research: (1) how to utilize information to one’s own advantage in strategic interactions; (2) how to mitigate losses resulting from information leakage to an adversary. In each part, I will demonstrate how the study of fundamental theoretical questions sheds light on executable solutions to real-world problems in security applications including, e.g., delivered software to the Federal Air Marshal Service for improving the scheduling of US federal air marshals. Finally, I will also mention how these ideas can be applied to other domains beyond security.
Bio: Haifeng Xu is a PhD candidate in the Computer Science Department at the University of Southern California, advised by Milind Tambe and Shaddin Dughmi. His research interests include artificial intelligence, computational game theory, algorithms, and applied machine learning. He focuses on developing theoretically grounded approaches that also have real-world impact.
Haifeng is a recipient of the 2017 Google PhD fellowship and the 2017 USC CAMS prize for excellence in research. His work has received the 2016 AAMAS best student paper award and the 2016 SecMas Workshop best paper award. Before USC, Haifeng obtained his Master in Computational Mathematics from the University of Waterloo in 2013 and his B.S. in Mathematics from the University of Science and Technology of China (USTC) in 2012.