Yuki Matsui
Papers
4
Total Citations
45
H-Index
3
About
Yuki Matsui is a pioneering researcher in human-robot interaction, specializing in affective computing and the generation of lifelike facial expressions for social robots. Her work centers on overcoming the limitations of conventional robotic systems, which rely on a fixed set of predefined expressions, by introducing dynamic, adaptive models. Matsui’s major contribution is the development of an interactive facial expression model based on the Simple Recurrent Network (SRN). This approach allows robots to generate a continuous, context-aware range of expressions in real time, enabling more natural and emotionally resonant face-to-face interactions with humans. Her most cited paper, "A Model for Generating Facial Expressions Using Virtual Emotion Based on Simple Recurrent Network" (2010, 24 citations), along with subsequent studies (totaling over 45 citations), has laid the groundwork for more responsive Kansei (emotionally expressive) robots. By treating humans as active receivers in a bidirectional emotional loop, Matsui’s research advances the field of socially assistive robotics, moving beyond static displays toward truly interactive artificial companions. Her work remains a key reference for engineers and cognitive scientists aiming to bridge the gap between mechanical form and human-like emotional communication.
Research Focus
Key Achievements
Top Papers
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