My primary research interests lie in artificial intelligence and reasoning under uncertainty, using logical and probabilistic models to analyze, forecast, and respond to agent behavior. I am also interested in time series analysis, big data integration, linear programming, and algorithmic game theory. I have developed several scalable probabilistic frameworks for behavioral modeling of international conflict and for identifying possible mitigating policies. Such issues provide unique, interdisciplinary challenges for expanding the field of artificial intelligence, but also opportunities for significant impact in security policy, international relations, and international development.
I am also interested more broadly in issues of technology policy and the social and security impact of ICT, particularly regarding governance and cybersecurity.
Some of my past and current research projects include:
- Decision-making Under Threat--Models of how media amplificaiton of violent events impacts public threat (mis)perception and the policy decisions of leaders that may cause persistent conflict.
- Cyber attacker behavioral models--Probabilistic models for forecasting attacker intentions in cyber attacks, facilitating better decision making regarding defensive resource allocation and potential counterintelligence activities.
- Cybersecurity Framework--Collaboration with the National Defense University Institute for National Strategic Studies to investigate a conceptual and strategic framework for cyberwar, focusing on the real and bureaucratic delineations between crime, espionage, and war.
- Actionable State Change Attempts--Framework for modeling the optimal response policy or counterstrategy to an agent's behavior, balancing the cost with likelihood of success.
- Technology Integration in the U.S. Intelligence Community--Investigating the technical and institutional barriers to technology integration in the Intelligence Community and assessing the needs for adaptive technologies.
- Stochastic Opponent Modeling Agents (SOMA)--Probabilistic logic modeling and reasoning framework for cultural dynamics. SOMA has been used primarily to model the behaviors of terror organizations, such as Hezbollah, Hamas, and Lashkar-e-Taiba, as well as the key players in the Afghan drug economy.
- SOMA Terror Organization Portal (STOP)--Online tool that provides national security experts, policy analysts, and political science researchers with access to data on terror organizations and the behavioral modeling and forecasting tools developed by LCCD.
- Change Analysis Predictive Engine (CAPE)--Probabilistic framework for modeling and forecasting when and how a group may change its behavior or strategies.