About
I am a postdoc researcher at the High Performance Computing Laboratory, part of the Institute of Information Science and Technologies of Italy’s National Research Council (CNR-ISTI). My main interests are in machine learning and network science, and I am now focused on temporal networks, spectral theory, and graph signal processing techniques for causal learning at scale.
I obtained my PhD in Artificial Intelligence from the University of Pisa in 2026, with a thesis on efficient (unsupervised) clustering of temporal graphs with high-dimensional features. It led to the development of a free and open-source library for temporal network analysis, along with contributions to graph modeling, graph neural networks, and GPU-accelerated algorithms.
Prior to that, my research was mostly in applied network science using OSINT frameworks. I have collaborated on projects with international organizations like UNICEF and the Education Commission, taught programming and computational social science courses in Italy and Brazil, and worked in software development and ML engineering for private clients in the industry.
My CV with work experience is available in its full version or in a one-page version (PDF). I also maintain a few other free open-source projects and write some less technical posts in a blog.
Recent updates
(Sep. 2026) Learning and Clustering on Temporal Graphs: Principles, Primitives, and Pooling. Presented at: ECML PKDD’26 – Nectar Track. Naples, Italy, Sep. 9, 2026.
(Aug. 2026) Toward Efficient Community Detection on Time-Varying Attributed Graphs. Presented at: Euro-Par’26 PhD Symposium. Best paper award. Pisa, Italy, Aug. 27, 2026.
(Aug. 2026) Accelerating Dynamic Graph Clustering on GPU Architectures with cuGraph. Presented at: Euro-Par’26 – FRAME Workshop. Pisa, Italy, Aug. 25, 2026.