Summary
Lorenzo Contento is a product engineer and applied mathematician with 8+ years of experience building mathematical and computational tools for statistical modelling in drug development. After a PhD and multiple postdoctoral positions in Japan and Germany, he developed and calibrated mechanistic ODE/PDE models for ecology and epidemiology, including COVID-19 forecasting with uncertainty quantification and wastewater data integration. At Pumas-AI he translates advanced numerical methods and hybrid modelling approaches (e.g., Universal Differential Equations) into practical software for industry. He combines deep expertise in mechanistic modelling, numerical simulation and MCMC-based inference with hands-on experience in machine/deep learning, synthetic-data training for medical imaging, and federated learning. Known for seeking concrete, challenging problems, Lorenzo bridges rigorous theory and production-ready tooling to make complex models usable in real-world decision making.
7 years of coding experience
7 years of employment as a software developer
Doctor of Philosophy - PhD, Applied Mathematics, Doctor of Philosophy - PhD, Applied Mathematics at Meiji University
Master's degree, Mathematics, 110/110 cum laude, Master's degree, Mathematics, 110/110 cum laude at Università degli Studi di Udine
110/110 cum laude, 110/110 cum laude at Scuola Superiore dell'Università degli Studi di Udine
Italian, English, Japanese