Auriel Washburn

UC San Diego Health System, University of California San Diego, Stanford University

Papers

Total Citations

H-Index

About

Auriel Washburn is a leading researcher in the field of human-robot interaction (HRI), with a specific focus on proximate, goal-directed joint action. Her work addresses the critical challenges that arise when humans and robots work side-by-side in shared physical spaces. Washburn’s major contributions include developing frameworks to understand and mitigate the impact of robot errors during close-proximity teamwork, a problem that is both common and disruptive. Her most-cited paper, "Robot Errors in Proximate HRI" (2020, 58 citations), examines how user expectations shape responses to robot mistakes, providing foundational insights for designing more resilient systems. She has also advanced the theoretical foundations of the field by proposing a comprehensive framework for proximate human-robot teaming (pxHRT) and exploring trust-aware control mechanisms. Notably, her work on "Anticipatory synchronization in artificial agents" (2017) integrates principles from physics, neuroscience, and cognitive science to harness self-organized coordination, pushing the boundaries of how robots can intuitively align with human partners. Through her research, Washburn is paving the way for safer, more effective, and more natural human-robot collaboration.