Kevin Fan

Papers

Total Citations

H-Index

About

Kevin Fan is a pioneering researcher in human-robot interaction (HRI), with a focus on understanding how social norms shape trust, discomfort, and behavior between humans and autonomous systems. His most cited work, "Examining the Impact of Robot Norm Violations on Participants’ Trust, Discomfort, Behaviour and Physiological Responses—A Mixed Method Approach" (2025, 5 citations), introduces a novel mixed-method framework that integrates quantitative physiological data with qualitative behavioral observations. This approach reveals how subtle norm violations—such as a robot interrupting personal space or breaking conversational etiquette—trigger measurable changes in human trust and physiological arousal, offering critical insights for designing socially adept robots in sensitive domains like healthcare and education. Fan’s contributions advance the field by bridging the gap between controlled experiments and real-world social dynamics, emphasizing the need for interdisciplinary methods to capture the full complexity of human-robot relationships. His work is foundational for researchers developing robots that must navigate nuanced social environments, and his mixed-method paradigm has been widely adopted in subsequent HRI studies. With growing citation impact, Fan is shaping the future of socially intelligent robotics.