Christopher Kiekintveld is an assistant professor at the University of Texas at El Paso. His research focuses on computational decision-making and tools for designing intelligent agents, particularly for complex multi-agent systems. He has made contributions that span multiple areas, including computational game theory, distributed optimization, risk analysis, adversarial reasoning, agent-based modeling and simulation, auctions, and trading agents. He received his Ph.D in 2008 from the University of Michigan for thesis work on trading agent design and strategic reasoning using simulation and empirical game modeling techniques. During this time he was a lead developer for Deep Maize, a champion agent designed for the Trading Agent Competition Supply Chain Management game. His most recent work applies game theory to real-world Homeland Security problems to generate unpredictable, risk-based resource allocation strategies. He has contributed to algorithmic advances that dramatically increase the scalability of game theory solutions for security resource allocation problems, and new modeling techniques that improve the robustness of solutions to many different kinds of uncertainty about the models and human behavior. The IRIS system based on this research is currently deployed by the Federal Air Marshals Service, and the GUARDS system developed for the Transportation Security Administration is currently under evaluation for nationwide deployment. The work was recently acknowledged with a best paper award at the top international conference on multi-agent systems, and was a finalist for the EURO excellence in practice award.