Papers
8
Total Citations
120
H-Index
6
About
Shogo Okada is a leading researcher in human-robot interaction (HRI), specializing in the development of socially intelligent robots capable of natural, adaptive communication. His work focuses on enabling robots to autonomously learn and interpret human nonverbal behaviors—such as gestures, gaze, and vocal cues—to facilitate seamless collaboration. A key contribution is his pioneering approach to unsupervised simultaneous learning of gestures and actions, allowing robots to detect commands and generate appropriate responses without explicit programming, a foundational paper with 55 citations. Okada has also advanced gaze control systems for human-like interaction and developed robots that can assess human internal states, such as speaking willingness, to adapt their interview strategies in real time. His research extends to healthcare, where he uses ubiquitous sensing and robot interaction to automatically classify dementia severity, demonstrating the practical impact of his work. With over 120 citations across his most influential publications, Okada’s innovations in incremental learning, multimodal sensing, and adaptive behavior generation are shaping the next generation of robots that can understand and respond to humans with unprecedented subtlety and effectiveness.
Research Focus
Key Achievements
Top Papers
- 1
- 2Autonomous development of gaze control for natural human-robot interaction19 citations · 2010
- 3
- 4Incremental learning of gestures for human–robot interaction13 citations · 2009
- 5
- 6
- 7A Platform System for Developing a Collaborative Mutually Adaptive Agent4 citations · 2009
- 8