Fuh‐Yu Chang

ITRI International, Industrial Technology Research Institute

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Total Citations

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About

Fuh-Yu Chang is a pioneering researcher in the field of human-robot interaction, with a focused expertise in robotic emotion recognition. His work centers on developing intelligent systems that enable robots to perceive and respond to human emotional states, thereby creating more natural and empathetic interactions. Chang’s major contributions include the creation of novel information fusion methods that combine audio and visual cues—specifically, facial expressions and speech signals—to achieve robust bimodal emotion recognition. His most cited paper, “A New Information Fusion Method for Bimodal Robotic Emotion Recognition” (2008), has garnered 29 citations and lays the groundwork for integrating multiple sensory inputs. This work is complemented by his 2007 study on SVM-based audio-visual fusion (17 citations) and a fast learning algorithm for adaptive emotion recognition (9 citations). Chang’s research is notable for its practical emphasis on real-time adaptability, allowing robots to function effectively across diverse users and environments. His achievements have advanced the frontier of socially intelligent robotics, making him a key figure in the development of machines that can genuinely understand human affect.