Francesco Pinto

PhD Student

​Francesco Pinto holds a BSc in Statistics and an MSc in Data Science from La Sapienza University of Rome. During his Master’s, Francesco also spent a semester at the University of Helsinki and completed his thesis at Eawag - the Swiss Federal Institute of Aquatic Science and Technology. At Eawag, his research focused on the impact of BatchNorm and LayerNorm on neural network initialization, studying how normalization layers influence training dynamics. 

Alongside his studies, Francesco worked as a Deep Learning Scientist Intern at the Swiss national weather service MeteoSwiss in Zurich, where he developed machine learning models for precipitation quality control. His work combined radar and ground measurements using deep learning techniques such as U-Nets and conditional neural processes. In his PhD, he aims to develop machine learning models for wind forecasting in order to help stabilize grids, reduce energy costs, and provide improved wind forecast models for the industry.