Yasir Tahir

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About

Yasir Tahir is a researcher at the intersection of human-robot interaction and social signal processing. His work centers on how humanoid robots can serve as social mediators, particularly in dyadic conversations. Tahir’s major contribution lies in developing real-time sociofeedback systems that quantify speech mannerisms and social behavior during two-person dialogs. His most-cited study (2018, 25 citations) presents a user evaluation of a Nao humanoid robot that provides this feedback, demonstrating how robots can subtly influence conversational dynamics. Earlier foundational work (2014, 14 citations) established the system’s architecture, where the robot analyzes participant behavior and determines when to intervene. This research has implications for assistive technologies, social skills training, and collaborative robotics. Tahir’s work is notable for bridging technical system design with empirical user studies, offering concrete evidence of how embodied agents can shape human social interaction. His findings are increasingly relevant as robots enter classrooms, therapy sessions, and workplaces.