Papers
26
Total Citations
353
H-Index
7
About
Tomoko Yonezawa is a pioneering researcher at the intersection of human-robot interaction, gaze tracking, and affective computing. Her work centers on creating socially aware robots that can perceive and respond to human nonverbal cues—particularly gaze—to enable more natural, intuitive communication. Yonezawa’s most influential contribution is her real-time, single-camera gaze estimation method (129 citations), which tracks facial features without requiring special calibration, making gaze-based interaction accessible for everyday robotic systems. She extended this technology into a series of gaze-communicative stuffed-toy robots, such as the GazeRoboard guide system, which use joint attention and eye contact to engage users in semipublic spaces. Her innovative Body-Emotion Model (BEM) explores how robots can express internal states through physiological phenomena like breathing and heartbeat, adding subtle emotional depth to robotic behavior. With over 300 total citations across her top papers, Yonezawa has demonstrated that even simple, soft robots can convey complex social signals—from emotional gripping to crossmodal awareness—paving the way for companion robots that feel genuinely responsive and alive.
Research Focus
Key Achievements
Top Papers
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- 8Emotional Gripping Expression of a Robotic Hand as Physical Contact7 citations · 2019
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