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About

Michael Pieroni is a leading researcher at the intersection of social robotics, human-robot interaction (HRI), and affective computing. His work focuses on endowing robots and smart objects with human-like social perception and emotional intelligence, enabling more natural and symbiotic interactions with people. Pieroni’s major contributions include the design and evaluation of a unique social perception system for HRI (35 citations), which allows robots to detect high-level features like facial expressions and context. He was a key contributor to the EASEL Project, which explored educational human-robot symbiotic interaction, developing a synthetic tutor assistant architecture (26 and 17 citations). Pieroni also pioneered the concept of the Affective Internet of Things (AIoT), where smart objects are given personality and emotional states (16 citations), and implemented Damasio’s somatic marker hypothesis for social robotics (14 citations). His work on context-aware attention systems for humanoid robots (7 citations) further demonstrates his commitment to creating perceptive, emotionally responsive machines. With a cumulative impact of over 115 citations, Pieroni’s research is shaping the future of socially intelligent robotics and ambient intelligence.