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About

Stefania Racioppa is a leading researcher in human-robot interaction, specializing in the development of long-term, adaptive social bonds between children and social robots. Her work is foundational to the ALIZ-E project, which explores how robots can sustain meaningful relationships with young users over time. Her most influential paper, "Multimodal Child-Robot Interaction: Building Social Bonds" (2013), has garnered over 206 citations and establishes key frameworks for robots to exhibit coordinated, context-aware social behavior. Racioppa’s research demonstrates that for robots to be effective companions, they must go beyond simple task completion to display familiarity and encourage personal disclosure. In her study "Young Users’ Perception of a Social Robot Displaying Familiarity and Eliciting Disclosure" (2015), she experimentally shows how specific verbal behaviors can strengthen user-robot relationships, a critical insight for designing engaging, long-term interactions. Her contributions are shaping the next generation of socially intelligent robots used in education, therapy, and child development, making her a pivotal figure in creating machines that not only interact, but genuinely connect.