Vincenzo Ventriglia
A results-driven data professional, focused on hype-free solutions tailored to business needs.
I currently create value at the National Institute of Geophysics and Volcanology, where I develop machine learning models in the Space Weather domain. My work is complemented by finding the hidden stories in data and make them accessible to stakeholders. I studied Physics in Italy (Napoli) and Germany (Frankfurt am Main), previously worked in Analytics within the strategic division of the world's largest professional services network, as well as in the Data Science department of Italy’s leading publishing group.
I am also an organiser of PyData Roma Capitale, actively involved in building the local Python and data science community. Outside of work, I enjoy theatre, discussing finance, and learning new languages.
Session
Have you ever happened to use GPS and realised that it is not working properly? The Sun could be responsible.
In this talk, I present a real-world machine learning forecasting system designed to predict a Space Weather phenomenon affecting GNSS accuracy and radio communications. The system is based on CatBoost and integrates data from space- and ground-based observations. SHAP is used to debug model behaviour and to build trust in model outputs. The talk focuses on model design and evaluation choices, showing how interpretability and uncertainty-aware forecasting can be combined in a real-time operational pipeline.