Kento Kuzushima
Papers
1
Total Citations
1
H-Index
1
About
Kento Kuzushima is a researcher focused on advancing human-agent interaction, particularly through the development of natural nonverbal behaviors in embodied conversational agents. His work addresses a critical challenge in robotics and virtual reality: enabling agents to exhibit lifelike gaze and motion during multi-party conversations. In his notable 2017 paper, "Conversational Agent Learning Natural Gaze and Motion of Multi-Party Conversation from Example," Kuzushima proposed a data-driven approach to model and replicate these subtle social cues from real human interactions. This contribution is foundational for creating more mindful and engaging daily interactions with embodied agents, as natural gaze and gesture are essential for trust and rapport. While his citation count is currently modest, his research sits at the intersection of computer vision, social robotics, and human-computer interaction, offering a promising pathway for future agents to seamlessly integrate into human social environments. Kuzushima's work underscores the importance of learning from example to bridge the gap between artificial and human-like communication.
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Top Papers
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