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About

Gianmaria Mancioppi is a researcher whose work sits at the intersection of human-robot interaction, affective computing, and assistive robotics, with a particular focus on improving quality of life for vulnerable populations. His most influential contribution, a comprehensive survey of behavioral models for social robots (2019, accumulating over 100 citations), has become a key reference point for researchers seeking to understand how robots can engage more naturally and effectively with humans. Alongside this, his work on unsupervised emotional state classification through physiological parameters (70 citations) demonstrates his commitment to enabling robots to perceive and respond to human emotional states in real time. Mancioppi has made notable strides in applying these technologies to healthcare, particularly in addressing mild cognitive impairment and Alzheimer's disease — conditions he identifies as urgent global challenges lacking effective pharmacological solutions. His studies on socially assistive robots for cognitive assessment and personalized care highlight a vision of robotics as a compassionate clinical tool. Further enriching this portfolio, his exploration of Laban Movement Theory for conveying robot emotion and his feasibility studies on user profiling reflect a deeply human-centered design philosophy. His cumulative body of work, exceeding 340 citations, positions him as an emerging voice shaping the future of socially intelligent robotics.