Pasquale Lisena

Pasquale Lisena is a Research Fellow in the Data Science department at EURECOM, where he contributes to the Data2Knowledge research group. His work bridges academic research with practical applications in knowledge-intensive domains.

Education:

• PhD in Computer Science from EURECOM / Sorbonne University (2019), thesis: "Knowledge-based music recommendation: Models, algorithms and exploratory search" supervised by Raphaël Troncy

His research centers on Knowledge Graphs, Knowledge Engineering, and Recommender Systems with strong applications in cultural heritage and music. Key specializations include:

• Semantic Web technologies for domain-specific knowledge representation
• Information extraction from multimedia and text sources
• Development of ontologies for complex cultural domains
• Music metadata modeling and recommendation systems

Recent publications reveal a trajectory from foundational music metadata work (2018-2019) toward cutting-edge applications in olfactory heritage (Odeuropa) and language model-driven recommendation (2025). His research consistently integrates knowledge graphs with machine learning, demonstrating expertise in both classical music informatics and emerging sensory heritage domains.

Awards:

• Best Resource Paper Award (2022) for Odeuropa Data Model publication

Funding and Collaboration:

• ANR JCJC project coordinator for kFLOW (2022-2024)
• Key contributor to EU H2020 projects including Odeuropa, SILKNOW, and MeMAD
• Extensive cross-institutional collaboration across European cultural heritage initiatives

He operates within EURECOM's Data2Knowledge group, participating in international research consortia focused on knowledge-intensive applications in cultural heritage preservation and digital humanities.