Professor Tambe's work focuses on advancing AI and multiagent systems for public health, conservation and public safety, with a track record of building pioneering AI systems for social impact. His research focuses on fundamental problems in computational game theory, machine learning, automated planning, intelligent agents, and multi-agent interactions that are driven by these topics, ensuring a virtuous cycle of research and real-world applications. This research has led to significant practical impact, such as use of the green security games framework to assist wildlife conservation around the world, use of social networks and machine learning to assist in improving public health outcomes such as HIV prevention, and the use of pioneering security games research for security optimization by agencies such as the US Coast Guard and the Federal Air Marshals Service.
