Giovanni Semeraro
Papers
4
Total Citations
18
H-Index
3
About
Giovanni Semeraro is a leading researcher at the intersection of artificial intelligence, social computing, and human-robot interaction. His work primarily focuses on developing intelligent systems that can understand, interact with, and recommend content to users in dynamic environments. A key contribution is his pioneering use of 2D Convolutional Neural Networks (CNNs) to detect bot accounts on Twitter by analyzing user-generated content, a method that has garnered 6 citations and addresses the critical issue of online misinformation and scams. Semeraro has also advanced the field of Conversational Recommender Systems (CoRSs), notably integrating them with humanoid robots to create more natural, dialog-based interfaces for tourism recommendations, as seen in his 2020 studies (5 and 4 citations respectively). His earlier work on a computational framework for emotion generation (3 citations) demonstrates a long-standing interest in making machines more empathetic. Through these contributions, Semeraro is shaping how AI can be both socially aware and practically useful, from filtering harmful bots to guiding travelers with robotic assistants.
Research Focus
Key Achievements
Top Papers
- 1
- 2
- 3Towards a Social Robot as Interface for Tourism Recommendations.4 citations · 2020
- 4Empathy: A Computational Framework for Emotion Generation3 citations · 2006