Papers
8
Total Citations
100
H-Index
5
About
Naoki Masuyama is a researcher specializing in affective computing, human-robot interaction, and computational intelligence, with a particular focus on bridging the gap between human emotional complexity and robotic systems. His most influential work centers on developing sophisticated emotional and personality models for humanoid robots, most notably his 2017 paper on personality-affected robotic emotional models with associative memory, which has garnered 49 citations and stands as his most recognized contribution to the field. Masuyama's research has consistently explored how psychological principles — such as mood congruency effects, the Pleasant-Arousal scaling model, and empathic response patterns — can be translated into functional robotic architectures. His studies demonstrate that effective human-robot communication demands not merely logical processing, but nuanced emotional responsiveness shaped by personality factors, mirroring the dynamics of human-human interaction. Beyond affective modeling, Masuyama has extended his expertise into autonomous mobile robotics, with recent work applying Adaptive Resonance Theory to global topological map building in unknown 3D environments. His foundational contributions also include Quantum-Inspired Bidirectional Associative Memory systems, enhancing memory capacity and recall reliability in interactive robots. With a body of work spanning over a decade, Masuyama remains a dedicated contributor to the evolving field of intelligent, emotionally aware robotic systems.
Research Focus
Key Achievements
Top Papers
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- 4Empathic Interaction Using the Computational Emotion Model10 citations · 2015
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