The symposium will review the scope and nature of game theory and adversarial reasoning within law enforcement, with a specific focus on the homeland security enterprise. The presentations will focus on the work of researchers who have performed studies and developed deployed applications of game theory for multiple components of the Department of Homeland Security.
Game theory provides an alternative to conventional decision making processes that allows us to reason about the responses of intelligent adversaries to security policies and resource allocations. Game-theoretic models can leverage the understanding that law enforcement officials have of adversary capabilities, goals, and historical patterns to improve decisions in complex homeland security and policing environments. One of the main aims of these models is to be able to effectively predict and react to the behavior of adversaries in different situations. The focus of the symposium will be on introducing the fundamental principles of these technologies, and providing examples where we bridge the gap between theoretical research and real-world practitioners.
The symposium will consist of four short lectures followed by Q & A sessions with attendees to discuss the current state of the field, as well as possible future applications and prospects.
Dr. Christopher D. Kiekintveld - The University of Texas at El Paso
Christopher Kiekintveld is an associate professor at the University of Texas at El Paso (UTEP). His research is in the area of intelligent systems, focusing on multi-agent systems and computational decision making. He is also interested in applications of artificial intelligence to homeland security, cybersecurity, trading agents, and other areas with the potential to benefit society. He received his Ph.D in 2008 from the University of Michigan for thesis work on strategic reasoning, including applications in designing a champion trading agent for the TAC SCM competition. He has worked on several deployed applications of game theory for security, including systems in use by the Federal Air Marshals Service and Transportation Security Administration. He has authored more than 60 papers in peer-reviewed conferences and journals (e.g., AAMAS, IJCAI, AAAI, JAIR, JAAMAS, ECRA). He has received several best paper awards, the David Rist Prize, and an NSF CAREER award.
Dr. Jun Zhuang - University of Buffalo
Dr. Jun Zhuang is an Associate Professor and Director of Undergraduate Studies, Department of Industrial and Systems Engineering at the University at Buffalo (UB). Dr. Zhuang has a Ph.D. in Industrial Engineering in 2008 from the University of Wisconsin-Madison. Dr. Zhuang's long-term research goal is to integrate operations research, game theory, and decision analysis to improve mitigation, preparedness, response, and recovery for natural and man-made disasters. Other areas of interest include applications to health care, sports, transportation, supply chain management, sustainability, and architecture. Dr. Zhuang's research has been supported by the U.S. National Science Foundation (NSF), by the U.S. Department of Homeland Security (DHS) through the National Center for Risk and Economic Analysis of Terrorism Events (CREATE) and the National Consortium for the Study of Terrorism and Responses to Terrorism (START), by the U.S. Department of Energy (DOE) through the Oak Ridge National Laboratory (ORNL), and by the U.S. Air Force Office of Scientific Research (AFOSR) through the Air Force Research Laboratory (AFRL). Dr. Zhuang is a recipient of the 2014 MOR Journal Award for the best paper published in 2013 in the journal Military Operations Research. Dr. Zhuang is a recipient of the UB's Exceptional Scholar--Young Investigator Award for 2013. Dr. Zhuang is also a fellow of the 2011 U.S. Air Force Summer Faculty Fellowship Program (AF SFFP), sponsored by the AFOSR, and a fellow of the 2009-2010 Next Generation of Hazards and Disasters Researchers Program, sponsored by the NSF.
Dr. Arunesh Sinha - University of Michigan
Dr. Arunesh Sinha is an Assistant Research Scientist in the Computer Science and Engineering Department at the University of Michigan. He received his Ph.D. from Carnegie Mellon University (CMU) and obtained his undergraduate degree in Electrical Engineering from IIT Kharagpur in India. He has industry research experience in the form of internships at Microsoft Research, Redmond and Intel Labs, Hillsboro. Dr. Sinha has conducted research at the intersection of security, machine learning and game theory. His interests lie in the theoretical aspects of multi-agent interaction, machine learning, security and privacy, along with an emphasis on the real-world applicability of the theoretical models. He was awarded the Bertucci fellowship at CMU for his innovative research. Dr. Sinha is the chair of two of the leading workshops at the intersection of Artificial Intelligence and computer security: AISec and AICS. Dr. Sinha's work has provided novel approaches to solve the optimization problem used in computing Stackelberg equilibrium in security games. This approach has solved large scale security games, where prior methods such as column generation completely fail to scale up. This innovative approach is being used in an airport screening application by TSA (called the DARMS project). Dr. Sinha has also provided mathematical foundations for the use of learning in security games, revealing the circumstances in which the composition of learning and optimization leads to sub-optimal outputs.