Alessandro Vinciarelli
Papers
10
Total Citations
107
H-Index
7
About
Alessandro Vinciarelli is a leading researcher at the intersection of social robotics, human-robot interaction (HRI), and nonverbal communication. His work systematically investigates how robotic gestures shape human perception, personality attribution, and user experience. Vinciarelli’s major contributions include demonstrating that modifying gesture parameters—such as amplitude and speed—directly influences Godspeed scores, a standard measure of user acceptance. He has also explored the similarity-attraction effect in HRI, showing that robots whose gestures match users’ personalities are perceived more favorably. His studies, involving dozens of participants and hundreds of gesture evaluations, have yielded highly cited papers (e.g., 23 and 22 citations) that are foundational for designing socially adept robots. Notably, Vinciarelli has extended this research across age groups—adolescents, young adults, and seniors—and robot types, including humanoids and androids. His recent work includes the HARPER dataset for 3D pose estimation from a robot’s perspective and applications of Perceptual Control Theory for user engagement. With over 100 citations across his top papers, Vinciarelli’s research is essential reading for students and scholars aiming to understand how robot behavior can be shaped to foster positive, intuitive human-robot relationships.
Research Focus
Key Achievements
Top Papers
- 1Shaping Robot Gestures to Shape Users' Perception23 citations · 2018
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