Y. C. Jessie

Papers

Total Citations

H-Index

About

Y. C. Jessie’s research lies at the critical intersection of human-robot interaction (HRI) and human-automation trust, with a focus on optimizing team performance in complex, multi-agent environments. Her work systematically quantifies how factors like robot reliability, autonomy level, and environmental context shape operator trust and decision-making. In her highly cited 2013 study (15 citations), Jessie demonstrated how varying levels of autonomy in a route-planning agent (RoboLeader) directly impacted human multitasking performance during multi-robot control and security tasks, using eye-tracking data to reveal cognitive load dynamics. This work provides foundational insights for designing adaptive automation in military and security operations. Her landmark 2011 meta-analysis (14 citations) is a cornerstone of the field, offering the first quantitative synthesis of human, robot, and environmental factors influencing trust development in HRI. By moving beyond qualitative reviews, Jessie provided a rigorous, data-driven framework that researchers and engineers now use to predict and calibrate trust in collaborative robots. Her contributions are essential for anyone designing effective, trustworthy autonomous systems for human-agent teams.