Samuele Millucci
Papers
1
Total Citations
3
H-Index
1
About
Samuele Millucci is a researcher at the intersection of human-robot interaction, affective computing, and artificial intelligence, with a focus on enabling machines to understand and respond to human emotions. His most-cited work, "Emotion recognition by facial image acquisition: analysis and experimentation of solutions based on neural networks and robot humanoid Pepper" (2023), explores how neural networks can be deployed on humanoid robots to accurately recognize emotions from facial expressions. This study not only advances the technical integration of deep learning with robotic platforms but also addresses the growing need for socially intelligent robots in daily assistance roles. With 3 citations, this work highlights Millucci’s contribution to making human-robot interaction more natural and empathetic. His research is particularly relevant as humanoid robots like Pepper become more common in healthcare, education, and service settings. By combining neural network-based emotion recognition with real-world robotic applications, Millucci is helping to bridge the gap between computational perception and meaningful social interaction, laying groundwork for more responsive and emotionally aware robotic systems.
Research Focus
Key Achievements
Top Papers
- 1