Papers

7

Total Citations

28

H-Index

3

About

Shiro Yano is a pioneering researcher at the intersection of cognitive science and robotics, whose work focuses on developing computational models of human attention to enable more natural human-robot interaction. His most significant contribution lies in the novel application of magic principles to robotics—analyzing how magicians manipulate spectators' attention to create computational models that allow robots to predict, guide, and redirect human focus during interactions. This innovative approach, detailed in his 2016 paper "Human Visual Attention Model Based on Analysis of Magic for Smooth Human–Robot Interaction" (11 citations), combines saliency map generation with top-down manipulation factors like human gaze and gestures. Yano's attention models, developed through multiple studies (2013-2014), represent a paradigm shift in robotics: rather than merely responding to human commands, his robots can proactively steer attention for smoother collaboration. He has also contributed to embodied-brain systems science and explored olfactory cues for motor learning. While his citation counts are modest, Yano's work is foundational for researchers seeking to bridge the gap between human cognitive mechanisms and robotic behavior, offering a unique, magician-inspired framework for intuitive human-robot teamwork.

Research Focus

Key Achievements

3
H-Index
7
Papers
28
Total Citations
4
Avg Citations/Paper
🏆 Most Cited Paper
Human Visual Attention Model Based on Analysis of Magic for Smooth Human–Robot Interaction
11 citations · 2016
📈 Most Prolific Year: 2014 (2 Papers)
🤝 Key Collaborators: 17
🏛 Institutions: Tokyo University of Agriculture and Technology, Ritsumeikan University, University of Tsukuba

Top Papers

  1. 1
  2. 2
  3. 3
  4. 4
  5. 5
  6. 6
  7. 7

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago