Advancing the science and engineering of human‑AI teaming through rigorous, human‑centered research — designing trustworthy AI teammates for defense, manufacturing, healthcare, and beyond.
"Advancing human‑AI teaming by understanding and optimizing collaborative systems comprising both human and computational elements to enhance performance and safety across manufacturing, healthcare, defense, and beyond."
Our interdisciplinary program integrates quantitative, qualitative, and computational methods to understand and improve human-AI collaborative systems.
Modeling information-sharing, team cognition, and workload to create synergistic human–machine partnerships across complex, high-stakes environments.
Designing transparent AI behaviors that accurately calibrate trust, support responsible AI adoption, and contribute to meaningful AI acceptance.
Improving skill transference from training to operations through intelligent interventions, human-centered design, and psychological fidelity.
Developing real-time adaptive interfaces that surface mission-critical cues and promote collective understanding in electronically contested environments.
Integrating collaborative robots and unmanned ground vehicles into advanced manufacturing workflows and high-stakes emergency response scenarios.
Developing rigorous experimental frameworks to test AI teammates' effectiveness, safety, and resilience through mixed-methods empirical research.
Published across leading venues in Human Factors, HCI, ACM, and IEEE.
A growing community of researchers advancing the science of human-AI collaboration at the University of Tennessee, Knoxville.
Interested in collaboration, graduate study, or partnership? We'd love to hear from you.