Alessandro Mazzei
Papers
7
Total Citations
27
H-Index
3
About
Alessandro Mazzei is a researcher whose work sits at the intersection of human-robot interaction (HRI), social robotics, and multimodal communication. His research focuses on developing more natural, empathic, and personalized interactions between humans and humanoid robots such as Pepper and NAO, with a particular emphasis on vulnerable populations including children with autism spectrum disorder. Among his most influential contributions is his investigation into how autistic children perceive and mentally model humanoid robots, work that has garnered 13 citations and highlights the therapeutic potential of social robots. Mazzei has also advanced the field through his exploration of adaptive emotional alignment in HRI, demonstrating that emotionally attuned robot dialogue can meaningfully influence user empathy and mental state attribution. His research on dynamic content personalization and multimodal speech-image coordination further pushes the boundaries of how robots can tailor communication to individual users, making interactions more engaging and effective. Mazzei's work on UX Personas for defining robot personality reflects a human-centered design philosophy that bridges engineering and user experience. His growing body of publications, spanning therapeutic robotics, persuasive communication, and educational applications, positions him as an emerging voice in the social robotics community with broad interdisciplinary reach.
Research Focus
Key Achievements
Top Papers
- 1Autistic Children's Mental Model of an Humanoid Robot13 citations · 2021
- 2Dynamic Personalization of Multimedia Content Based on User Model3 citations · 2024
- 3Multimodal Strategies for Robot-to-Human Communication3 citations · 2024
- 4UX Personas for defining robot's character and personality3 citations · 2022
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- 7Towards a Structured Multimodal Speech-Image Coordination1 citations · 2025