Max Robotics — Global Service Robot Directory + US Certification

About

Wei Fen Hsieh is a researcher in human-robot interaction (HRI), specializing in how robots can perceive, interpret, and respond to human nonverbal behavior to create more natural and socially aware communication. Her work focuses on enhancing robot expressiveness and social intelligence, particularly for platforms like the humanoid robot Pepper. Hsieh’s major contributions include developing methods for customizable robot motion to improve user familiarity and social learning, as well as analyzing nonverbal cues—such as gestures and vocal features—to detect awkward or uncertain social situations. She has also pioneered techniques for robots to both express and identify human confidence levels using verbal and nonverbal features, enabling more adaptive and empathetic interactions. Her most-cited paper (5 citations) on customizable motion for Pepper demonstrates her practical approach to making robots more relatable and user-friendly. With additional works on awkwardness detection (4 citations) and confidence recognition (2 citations), Hsieh’s research provides foundational insights into building robots that can navigate the subtleties of human social dynamics, advancing the field toward more intuitive and emotionally aware robotic companions.