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About

Mingyang Shao is a pioneering researcher at the intersection of socially assistive robotics and human-robot interaction, with a focus on promoting physical health and emotional well-being. Their work centers on developing robots that can detect, interpret, and respond to human affect during exercise, making fitness more engaging and accessible. Shao’s most cited paper (31 citations) introduces “Salt,” an affect-aware social robot that provides real-time encouragement during upper body workouts, demonstrating how robotic empathy can enhance motivation. A subsequent study (23 citations) advances affect elicitation techniques for training robots to recognize user emotions, a critical step toward natural HRI. Shao has also explored long-term exercise adherence among seniors (15 citations), comparing group and one-on-one interactions to combat age-related inactivity. More recently, their research extends to industrial applications with a metamorphic mechanism-based robot for climbing wind turbine blades (2 citations), showcasing versatility in robotic design. With a growing citation footprint and a clear commitment to improving quality of life through intelligent, empathetic machines, Shao is shaping the future of robots as both companions and coaches.