I am an associate professor in the Data Engineering, Science and Systems (DESS) group at Aalborg University. My research lies at the intersection of knowledge graphs, artificial intelligence and data privacy, with the goal of enabling reliable and scalable analysis of heterogeneous and dynamic data.

I design methods that combine AI and knowledge graphs to extract, structure and analyse data while preserving privacy, with a particular focus on health applications. I contribute to the HEREDITARY project, where I investigate knowledge graph-based approaches to privacy-preserving federated analytics, and lead the AI:HealthData project, which explores how clinical data can be transformed into structured, interpretable representations to support decision-making.

My research builds on more than a decade of experience in the Semantic Web, dynamic knowledge graphs, and privacy‑aware data science, bridging data management and machine learning. I obtained my PhD from Politecnico di Milano with a thesis on a formal reference model for stream reasoning systems. During my PhD, I spent research periods at IBM Research Ireland and WU Vienna, and I was awarded an IBM PhD Fellowship (2014/15).

Before joining Aalborg University, I was a postdoctoral researcher at the University of Zurich, and a research fellow at the University of Aberdeen. Earlier, I gained industrial experience working as a junior researcher and consultant at CEFRIEL.

My research has received international recognition, including the Best Paper Award at ADBIS 2025 and Best Poster Awards at ISWC 2018 and 2019. I have also contributed to several award-winning Semantic Web systems in the area of smart cities and social media analytics.