Mario De Florio

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Mario De Florio’s research focuses on scientific machine learning in a physics-informed fashion for innovative research in renewable energy. He has expertise in mathematical modeling of complex systems, collaborating with subject matter experts in a variety of fields, such as neuroscience, pharmacokinetics, systems biology, chemical kinetics, nuclear dynamics, energy systems, and many more, to help understand the underlying phenomena using first principles and experimental data.

Research Interests

Physics-informed machine learning

Time series analysis

Physics discovery

Neural networks

Dynamical systems

Professional Experience

Postdoctoral Research Associate, Brown University (2023–2024)

Graduate Research Associate, The University of Arizona (2020–2022)

Education/Academic Qualification

PhD, Systems and Industrial Engineering, University of Arizona

Master, Energy and Nuclear Engineering, University of Bologna

Bachelor, Energy Engineering, University of Bologna

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