Marco Viviani

Marco Viviani is a researcher affiliated with the University of Milano-Bicocca and has published extensively in the fields of Information Retrieval, Health Misinformation Detection, and Social Media Credibility. His work leverages Artificial Intelligence, Natural Language Processing, and Privacy Analysis to address challenges in digital health, misinformation, and data ethics. He actively contributes to workshops like ROMCIR (Reducing Online Misinformation Through Credible Information Retrieval) and collaborates with researchers such as Gabriella Pasi, Rishabh Upadhyay, and Marinella Petrocchi.

Research Interests focus on combating health misinformation through LLMs and Knowledge Graphs, enhancing Truthful Consumer Health Search, and analyzing Privacy Risks in social media. His methodologies include Zero-Shot Prompting, Transformer-Based Re-ranking, and Quantifier-Guided Aggregation.

Recent publications at venues like ECIR, CLEF, and WI-IAT highlight his contributions to Document Sanitization, Long Document Classification, and Gender-Inclusive Language automation. Despite no explicit awards listed, his prolific output (104 records since 2004) underscores his impact in Digital Health, Misinformation Mitigation, and Responsible AI.