Working at the edges of network virtualization,
distributed systems, and orchestration.
I'm a master's student in Telecommunications Engineering at the Università di Bologna, currently on a research internship at Télécom Paris. My work sits at the intersection of network virtualization and machine learning — specifically, how we model the behavior of complex cloud-native systems in ways that are faithful, tractable, and actually useful.
I firmly believe knowledge is power. In virtualized environments, to know is to observe — my research focuses on building a multi-purpose observation tool that exposes metrics for optimization and management purposes.
I'm looking to continue this line of work in a Ph.D. program starting fall 2026.
Training Mixture Density Networks on performance traces collected from Kubernetes microservice environments. The goal: a learned component that reproduces the stochastic latency behavior of a live cluster well enough to stand in as a digital twin. Latencies modeled with Weibull output distribution to better capture tail behavior; traces collected via Jaeger with controllable HTTP injection.
Work from my internship at Télécom Paris will be added here as it becomes publishable. Check back, or reach out if you're curious about something specific.