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 (ISTI-CNR). My interests are in machine learning and network science with a focus on temporal networks, especially spectral theory and graph signal processing techniques for causal learning at scale.
In my doctoral research, I studied efficient algorithms and neural models for (unsupervised) clustering of temporal graphs with high-dimensional features. It led to advancements in pattern recognition and GPU acceleration, and generative block models for principled benchmarking.
Prior to the PhD, 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 with software development and ML engineering in academic and industry settings.
My CV with work experience is available here and a list of recent contributions is found here. I also maintain a few free¹ open-source² projects³ and write some less technical posts in a blog.
Recent news
(July 2026) Learning and Clustering on Temporal Graphs: Principles, Primitives, and Pooling. Accepted: ECML PKDD’26 – Nectar Track. Naples, Italy, Sep. 7–11, 2026.
(June 2026) Accelerating Dynamic Graph Clustering on GPU Architectures with cuGraph Preprint. Accepted: FRAME – Euro-Par’26. Pisa, Italy, Aug. 24–28, 2026.
(June 2026) Toward Efficient Community Detection on Time-Varying Attributed Graphs Preprint. Accepted: Doctoral Symposium of Euro-Par’26. Pisa, Italy, Aug. 24–28, 2026.
(June 2026) Dynamic Graph Clustering with Graph Neural Networks. Poster presented at: Learning on Graphs – Italian Meetup (LoG’26@Pisa). Pisa, Italy, June 9–11, 2026.