Adam Fouse
Papers
2
Total Citations
9
H-Index
2
About
Adam Fouse is a leading researcher at the intersection of artificial intelligence, human-machine teaming, and organizational design. His work fundamentally addresses how heterogeneous teams—composed of humans and autonomous agents—can be dynamically structured to tackle complex, high-stakes missions, from disaster relief to cyber reconnaissance. Fouse’s major contributions include pioneering frameworks for active learning and structure adaptation in these mixed teams, enabling them to self-organize and respond to evolving operational demands. His most cited paper, "Active learning and structure adaptation in teams of heterogeneous agents" (2018, 5 citations), lays the groundwork for designing the organizations of the future, directly informing Department of Defense strategies. More recently, his transdisciplinary approach in "Transdisciplinary Team Science" (2023, 4 citations) breaks new ground by integrating insights from multiple disciplines to create artificial social intelligence for seamless human-agent collaboration. By bridging theoretical models with practical DoD applications, Fouse is shaping how next-generation teams are conceived, built, and deployed, making his work essential for researchers in AI, cognitive science, and defense innovation.
Research Focus
Key Achievements
Top Papers
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