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Personal Profile
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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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