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About

Teruhisa Misu is a researcher whose work spans human-robot interaction, spoken dialogue systems, and the emerging field of prosocial behavior in autonomous mobility. His early contributions focused on situated language understanding in dynamic environments — most notably within moving vehicles — where he developed methods enabling users to query information about surrounding buildings in real time, a challenge addressed in his influential 2014 work on language understanding at driving speeds. Alongside this, Misu made significant strides in robot speech synthesis, pioneering cloud robotics-based approaches that replaced monotonous text-to-speech outputs with more naturalistic, dialogue-oriented communication modeled on hidden Markov methods, work that attracted considerable attention with nearly 20 citations each. In recent years, Misu has shifted toward understanding how humans and autonomous agents — including delivery robots and e-scooters — can coexist harmoniously in urban spaces. His research explores how prosocial norms can be cultivated through observational learning and immersive virtual environments, and how post-ride feedback might encourage more considerate micromobility behavior. His 2024 study on prosocial norms toward delivery robots reflects a growing societal urgency in this domain. Across his career, Misu demonstrates a consistent commitment to making autonomous systems more socially intelligent and human-centered.