Masayuki Fujiwara

Japan Advanced Institute of Science and Technology

Papers

1

Total Citations

3

H-Index

1

About

Masayuki Fujiwara is a pioneering researcher at the intersection of cognitive neuroscience and human-robot interaction, specializing in the methodological design of real-world neurobehavioral studies. His most cited work, “Methodological Design for Integration of Human EEG Data with Behavioral Analyses into Human-Human/Robot Interactions in a Real-World Context” (2019), has garnered 3 citations and represents a foundational contribution to ecologically valid neuroergonomics. Fujiwara’s major contribution lies in developing a robust framework that synchronizes mobile EEG recordings with behavioral metrics during naturalistic social exchanges—both between humans and between humans and robots. This approach enables researchers to capture neural correlates of social cognition outside the confines of traditional laboratory settings, bridging a critical gap in understanding how the brain processes dynamic, real-world interactions. His work has significant implications for designing more intuitive and responsive social robots, as well as for advancing clinical applications in social neuroscience. By demonstrating that high-quality EEG data can be collected during unconstrained, interactive scenarios, Fujiwara has opened new avenues for studying human social behavior and human-robot collaboration in authentic environments. His methodological innovations continue to influence the fields of cognitive engineering, social robotics, and neuroergonomics.

Research Focus

Key Achievements

1
H-Index
1
Papers
3
Total Citations
3
Avg Citations/Paper
🏆 Most Cited Paper
Methodological Design for Integration of Human EEG Data with Behavioral Analyses into Human-Human/Robot Interactions in a Real-World Context
3 citations · 2019
📈 Most Prolific Year: 2019 (1 Papers)
🤝 Key Collaborators: 9
🏛 Institutions: Japan Advanced Institute of Science and Technology

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 11 days ago