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About

Patrick Gebhard is a distinguished researcher whose work sits at the intersection of human-robot interaction, affective computing, and socially interactive agents. His contributions span multiple domains, from foundational models of social cognition to applied systems in industrial and clinical settings, making him a uniquely versatile figure in intelligent systems research. Gebhard's early influential work on gaze modeling for grounding in multimodal human-robot interaction (65 citations) established key principles for enabling robots to engage in natural social collaboration. This research recognized that effective HRI demands nuanced communicative behaviors—not simply functional responses. He subsequently extended these insights into affective and emotional dimensions, contributing models of trust, empathy, and flow states for socially interactive robots. A significant thread of his research addresses worker well-being in cobot environments. His scoping review on physical and mental health in collaborative robotics (40 citations) and related control architectures demonstrate a commitment to human-centered design in industrial automation. More recently, Gebhard has explored the affective capabilities of large language models (21 citations), probing ChatGPT's zero-shot performance on emotion-related tasks—a timely and impactful direction. His work on neurorehabilitation robots and serious games further highlights his interdisciplinary reach, applying socially interactive agents to support vulnerable populations. Across these domains, Gebhard consistently bridges technical innovation with genuine human need.