Mario De Florio received his BSc and MSc in Energy & Nuclear Engineering from University of Bologna in 2016 and 2019, respectively. He earned his PhD in Systems & Industrial Engineering at the University of Arizona in 2022, where he focused on optimization algorithms for parameter estimation of meteorites and asteroids, and developing physics-informed machine learning frameworks for applications in photon transport, rarefied gas dynamics, and stiff chemical kinetics. In 2023, Mario began his role as a Postdoctoral Research Associate in the Division of Applied Mathematics at Brown University. There, he advanced physics-informed machine learning algorithms for dynamical system identification from time-series data, with applications in systems biology, cardiovascular modeling, chaotic systems, and energy systems. Most recently, in September 2024, Mario joined the National Renewable Energy Laboratory (NREL) to further his research in cutting-edge machine learning techniques for innovative advancements in renewable energy.
