Lorenzo was among the first cohort of graduates in Mathematical and Computing Sciences for Artificial Intelligence at Bocconi University (Milan). During his undergraduate studies, he conducted research at the University of Oxford, analyzing spatial transcriptomics data, and at Institut Pasteur as an AMGEN scholar, where he developed deep learning models for microscope image analysis.

Lorenzo's research focuses on applying deep generative models at the intersection of structural biology and immunology, with a particular interest in protein and small molecule design. He is also interested in Scientific Machine Learning and Bayesian Optimization.

He completed an internship and his master's thesis at Roche (Basel), where he worked on developing algorithms for reaction condition prediction to accelerate early drug development.

Beyond academia, Lorenzo is passionate about cooking and enjoys long hikes of multiple days in nature.