Jeff Rousseau

Papers

Total Citations

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About

Jeff Rousseau is a leading researcher in the field of human-robot teaming, with a specific focus on developing coordination and interaction frameworks for complex, high-stakes environments. His work primarily addresses the integration of autonomous systems into small dismounted teams, particularly for applications like building surveillance and room clearing. Rousseau’s key contributions center on creating agent-based coordination models that enable effective collaboration between humans and multirobot teams in dangerous urban settings. He introduced the Context for Human and Automation Teams (CHAT) model, a novel framework designed to represent context at a level of abstraction that is actionable for both human operators and automated systems, thereby improving mixed-initiative decision-making. His research on multimodal interaction for human-robot teams has further advanced how soldiers and first responders can intuitively command and cooperate with unmanned ground vehicles. While his most-cited works—including his 2010 paper on agent-based coordination (8 citations) and his 2013 work on multimodal interaction (5 citations)—reflect a focused and impactful career, his development of the CHAT model stands out as a notable achievement in the field. Rousseau’s work is foundational for anyone studying the practical deployment of autonomous systems in military and public safety operations.