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About

Yuki Muto's research lies at the intersection of human-robot interaction, affective computing, and personalized recommendation systems, with a particular focus on creating more natural communication between humans and robots in everyday environments. Muto pioneered the use of sentiment analysis to generate user profiles from television watching behavior, a novel approach that enables systems to understand viewer preferences and emotional responses without explicit input. This foundational work, published in 2007 and accumulating over 20 citations, demonstrated how Web intelligence techniques could be applied to make TV program recommendations more personalized and context-aware. Muto extended this concept to human-robot communication, developing systems where partner robots could use TV program recommendations as a basis for social interaction and support. The "Humatronics" framework, introduced in 2008, proposed a new paradigm for designing electronic systems—including robots and computers—that reduce the burden on elderly and disabled users by creating more symmetrical, intuitive relationships between humans and technology. Muto's work on artificial visual perception for autonomous robots, inspired by early biological visual processing, further contributed to efficient scene understanding. Through these interconnected contributions, Muto has advanced the vision of socially assistive robots that can understand and respond to human interests and emotions in natural, everyday settings.