Diane Lee
Papers
1
Total Citations
7
H-Index
1
About
Diane Lee is a pioneering researcher at the intersection of human-robot interaction, team cognition, and neuroergonomics. Her work fundamentally explores how humans and autonomous systems collaborate under high-stakes conditions, with a particular focus on trust dynamics, team performance, and neurophysiological synchrony. In her landmark 2023 study, “All Human Versus Human-Robot Teaming: Measuring Neurophysiological Synchrony, Team Performance, and Trust during Search and Rescue,” Lee employed a Wizard of Oz approach within a multiplayer virtual environment to directly compare all-human teams against human-robot teams. This work, already garnering 7 citations, revealed critical insights into how trust networks and neural coupling differ when a quadruped robot joins the team. By measuring real-time neurophysiological synchrony alongside behavioral metrics, Lee provides a novel framework for understanding the subtle, often invisible, mechanisms that underpin effective human-robot collaboration. Her research has profound implications for designing future autonomous systems in domains like disaster response, military operations, and healthcare, where seamless human-robot teaming can mean the difference between success and failure. Lee’s contributions are shaping how we build and evaluate the next generation of intelligent, trustworthy robotic teammates.
Research Focus
Key Achievements
Top Papers
- 1