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About

Paul Saulnier is a pioneering researcher in Human-Robot Interaction (HRI), with a focused interest in how robots can socially and nonverbally interrupt humans during collaborative tasks. His work sits at the intersection of social robotics, nonverbal communication, and bio-electrical signal processing. Saulnier’s major contributions include demonstrating how low-cost bio-signal devices—such as those reading facial muscle tension or skin biopotential—can influence the social behaviors of domesticated robots, a concept explored in his most-cited paper (30 citations). He also systematically investigated minimal nonverbal interruption cues in HRI, examining how a robot’s speed of motion, proximity, and orientation can effectively initiate an interruption without verbal commands (29 citations). Through Wizard of Oz studies, Saulnier advanced understanding of how robots should time and express interruptions in domestic settings, laying groundwork for more intuitive and socially graceful robotic assistants. His research, though early in citation impact, is foundational for designing robots that can seamlessly integrate into human environments, making him a notable contributor to the emerging field of socially aware robotics.