Antonio obtained a BSc degree  cum laude in Environmental Engineering at the University of Firenze, with a thesis on hydrological modelling for mountain basins.  He then moved to the Netherlands, where he graduated cum laude in the MSc programme Civil - Hydraulic Engineering at TU Delft. For his master's thesis in collaboration with Deltares, he developed an innovative deep-learning model for predicting the morphological changes of braided rivers. During his master studies he also worked as teaching assistant for a master course on modelling and data science for engineering and a master course on stakeholder engagement in river engineering. Prior to joining EPFL, he spent six months as researcher at the University of Liège, investigating strategies for numerical modelling of floating debris dynamics in channels.

My PhD project focuses on river morphodynamics. Specifically, I investigate the evolution of fluvial bedforms and the associated quantification of sediment transport through numerical modelling and analysis with data-driven algorithms. Besides this, I am interested by the integration between traditional and innovative modelling tools for river hydraulics and morphology. For instance, building up on my master's thesis research, I aim to combine satellite images with deep learning models for predicting the planform changes of rivers.