Takuya Tsujimoto
Papers
2
Total Citations
21
H-Index
2
About
Takuya Tsujimoto is a researcher in human-robot interaction, focusing on how robots can recognize, generate, and express emotions to communicate naturally with humans. His work centers on Interactive Emotion Communication (IEC), a framework that integrates emotion estimation and emotional gesture generation in real-time. In his highly cited 2016 paper, he proposed using a recurrent neural network (RNN) combined with Russell’s circumplex model to enable robots to both infer human emotions and produce appropriate emotional responses, moving beyond hand-crafted designs. His 2017 study further explored how emotional expressions from real humanoid robots influence human decision-making, demonstrating that a simple fuzzy inference model can capture this effect. With over 20 citations across his key works, Tsujimoto’s research bridges affective computing and robotics, offering practical pathways for more intuitive and empathetic human-robot communication. His contributions are particularly valuable for developing socially assistive robots and interactive systems that require nuanced emotional engagement.
Research Focus
Key Achievements
Top Papers
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