Makoto Motoki
Papers
4
Total Citations
11
H-Index
3
About
Makoto Motoki is a researcher whose work spans the fascinating intersection of robotics, human-computer interaction, and neural computation. His key research areas include project-based learning (PBL) in embedded systems, human-robot interaction through non-verbal communication, and artificial neural networks. Motoki made significant contributions by proposing an interdisciplinary PBL curriculum using the Embedded System Symposium robot challenge, offering a practical framework for teaching software development through hands-on robot design. He also pioneered "presence expression" using eye robots to create more intuitive and empathetic interfaces for daily-life support systems, and developed "AHOGE" (Antenna Hair-type Object for Generating Empathy), a novel component that uses expressive motions based on the pleasure-arousal plane to foster emotional connections between humans and technology. In neural networks, Motoki proposed a Hebbian learning rule for pulse neural networks that effectively restrains catastrophic forgetting, allowing new patterns to be learned without overwriting past knowledge. While his most-cited papers each hold 2–3 citations, their interdisciplinary nature—bridging education, robotics, and AI—demonstrates a unique vision for creating more human-centered and adaptive intelligent systems.
Research Focus
Key Achievements
Top Papers
- 1An Interdisciplinary and University PBL Curriculum Using Robot Challenge3 citations · 2018
- 2Presence expression using eye robot for computer go and system3 citations · 2011
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