Fabio Persia

Fabio Persia is a Professor at the University of Naples Federico II with an extensive publication record spanning 15 years (2009-2025), demonstrating continuous academic engagement. His research portfolio spans multiple institutions through collaborations with over 70 co-authors, most notably Daniela D'Auria (43 publications), Mouzhi Ge (17), and Giovanni Pilato (14).

Dr. Persia's research interests focus on the intersection of semantic computing, event processing, and practical applications. His work evolved from foundational contributions to multimedia recommender systems (2013) to developing the ISEQL interval-based surveillance event query language (2016), and most recently to healthcare AI applications. He has pioneered complex event processing frameworks for video surveillance, created multi-agent systems for epilepsy detection (PredictMed-epilepsy), and explored social sensing for personalized routing during the pandemic. His recent work increasingly integrates large language models with healthcare monitoring systems, reflecting current AI trends.

Analysis of his publication trends since 2020 reveals a strong healthcare focus (65% of recent work), particularly in patient monitoring architectures, clinical decision support, and medical AI integration. His publications demonstrate consistent methodological rigor across domains, often combining semantic computing with real-time event processing to address practical challenges in healthcare and social computing contexts.

Dr. Persia has served as guest editor for six special issues in the International Journal of Semantic Computing (2023-2025) covering Robotic Computing, Transdisciplinary AI, and Multimedia Computing, confirming his leadership in these research communities. His editorial roles complement his extensive publication record, which includes 25 journal articles and 76 conference papers.

His collaborative research includes significant projects with Stefania Costantini on patient monitoring systems, with Mouzhi Ge on multimedia recommenders, and with Sven Helmer on interval joins and event detection. While specific grant information isn't detailed in publications, his sustained output suggests successful funding from multiple sources. His current research trajectory indicates growing emphasis on LLM integration in medical contexts and context-aware systems for public health applications.