Pietro Bongini received his Ph.D. degree in Smart Computing from the University of Florence in 2022, with a thesis titled "Graph Neural Networks for Molecular Data". He had previously obtained a Master's Degree in Information Engineering with a thesis on Artificial Intelligence from the Department of Infomation Engineering and Mathematics of the University of Siena, in 2018, achieving a 110/110 with Honours. 

After receiving his Ph.D., he started a Post-Doc at the Department of Informatics of the University of Pisa, where he developed various research software solutions for statistical anlysis and machine learning predictions on the outcomes of rare diseases and BPCO, in collaboration with Chiesi Farmaceutici S.p.A, also combining machine learning predictors with genetic algorithms.

During his Ph.D. and his Post-Doc period he worked on Graph Neural Networks (GNNs), both from a theoretical point of view and an application-oriented one. In particular he focused on biological applications of GNNs and on the development of Graph Generative Models based on GNNs for the generation of new molecular structures. He also applied GNNs to the prediction of Drug Side-Effects and devised a new framework for the development of Composite Graph Neural Networks (CGNNs) for processing molecular data with minimal information loss, and other works.

He joined the VIPP group on September 01, 2024, as a Junior Assistant Professor (RTDA), working on the FF4ALL research project, funded through the PNRR (National Recovery and Resilience Plan) program.