About

Alfredo Cuzzocrea’s research sits at the intersection of human-robot interaction, emotion recognition, and big data analytics, with a strong focus on developing intelligent, empathetic systems. His major contributions include pioneering a taxonomy-based framework for detecting user emotions in artificial intelligence applications—a foundational paper with 14 citations—and a composite system that enables social robots to analyze and respond to human emotional cues. Cuzzocrea has also advanced real-time detection and mining of streaming microblog posts, and he developed a genetic-fuzzy algorithm inspired by mirror neurons to enhance human-machine interfaces in big data settings. His work on scan-matching algorithms for tracking moving objects further integrates robotics with big data. Notably, he has created and assessed an Italian textual dataset for emotion recognition in human-robot interactions, leveraging ChatGPT to build ad-hoc dialogues. With a portfolio that spans gesture acquisition for humanoid robots and pattern recognition in complex environments, Cuzzocrea’s research is shaping the next generation of socially aware robots and intelligent systems.

Research Focus

Key Achievements

5
H-Index
9
Papers
56
Total Citations
6
Avg Citations/Paper
🏆 Most Cited Paper
Taxonomy-Based Detection of User Emotions for Advanced Artificial Intelligent Applications
14 citations · 2018
📈 Most Prolific Year: 2021 (2 Papers)
🤝 Key Collaborators: 11
🏛 Institutions: University of Trieste, University of Calabria, Laboratoire Lorrain de Recherche en Informatique et ses Applications, Université Paris Cité

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago