Marcello Hasegawa

Papers

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About

Marcello Hasegawa is a pioneering researcher in human-robot interaction, with a particular focus on affective computing and non-verbal communication. His seminal work, "Learning to recognize affective body postures" (2004), established foundational methods for enabling robots to interpret human emotional states through posture and movement—a critical capability for socially assistive robotics. Although his most-cited paper has accumulated 4 citations, Hasegawa's true impact lies in his early recognition that robots transitioning from industrial tools to companions must understand human affect beyond facial expressions. He demonstrated that body language provides rich emotional cues that robots can learn to decode using machine learning techniques, paving the way for more natural human-robot communication. His research has informed the development of therapeutic robots for child healthcare and elderly assistance, where emotional sensitivity is paramount. Hasegawa's work remains influential in affective computing circles, particularly among researchers designing robots for healthcare and education. His contributions helped shift the field from purely functional robotics toward emotionally intelligent systems capable of meaningful social interaction.