Thomas Pellegrini

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About

Thomas Pellegrini is a leading researcher in affective computing and human-robot interaction, with a particular focus on group emotion recognition and entertainment robotics. His most-cited work, "Group emotion recognition strategies for entertainment robots" (2018, 44 citations), introduces a pioneering system that analyzes facial expressions to determine the collective emotional state of a group—a critical capability for social robots operating in public or interactive settings. By bridging general emotion models with practical, real-time recognition strategies, Pellegrini has advanced how robots perceive and respond to human social dynamics. His contributions are foundational for developing more empathetic and context-aware autonomous systems, especially in entertainment and service robotics. Pellegrini’s research not only pushes the boundaries of machine perception but also addresses key challenges in deploying robots that can engage naturally with multiple users simultaneously. His work continues to influence the design of socially intelligent agents, making him a notable figure in the intersection of computer vision, human-robot interaction, and affective computing.