Gloria Lorenzetti graduated in Mathematics in 2016 at the University of Padua, discussing a thesis on smoothing techniques, functional principal components analysis (PCA) and principal differential analysis(PDA), in cooperation with Aprilia Racing.
She was research fellow, from 2016 until mid-2018, at the Departement of Civil, Architectural and Environmental Enginerring at the University of Padua, working on Computer Vision and 3D digital stereophotogrammetry techniques.
Since the end of 2018 she collaborates with M3E, dealing with computer vision and 3D digital stereophotogrammetry techniques, data analysis by means of Machine Learning algorithms and optimization problems.