We have organized our projects into three large domain areas: 1) social work, public health, and medical decision making, 2) conservation, and 3) safety and security. Our recent research on the combating the COVID-19 pandemic is also listed above as a fourth category. Please click on the icons above to view more specific projects.
We focus on fundamental research problems in computational game theory, machine learning, automated planning, intelligent agents and multiagent interactions driven by real world challenges, ensuring a virtuous cycle of research and real-world applications. Examples of research driven by real-world problems include algorithms that enable influence maximization in social networks under dynamism and uncertainty, challenges of learning and handling bounded rationality models of human (adversary) behavior from real-world data, solving massive scale games uncertainty, and others.