Carlo Fiorina

Carlo Fiorina is an Associate Professor of Nuclear Engineering at Texas A&M University, affiliated with the Computational and Data Sciences Applied to National Security and Nuclear Engineering groups. His work focuses on high-fidelity numerical methods, advanced reactor design, and open-source software development for nuclear systems. Fiorina holds a Ph.D. in Energy and Nuclear Science from Politecnico di Milano, alongside M.S. and B.S. degrees in Nuclear and Electrical Engineering.

Research Interests
Fiorina's research spans thermal-hydraulics simulation, neutronics modeling, and uncertainty quantification for fusion and fission systems. He specializes in multiphysics coupling frameworks (e.g., GeN-Foam, MOOSE) and has pioneered dynamic mesh deformation techniques for fuel performance analysis. His work integrates machine learning for reduced-order modeling, accelerating simulations of complex phenomena like sodium boiling in fast reactors.

Awards

• Early Career Reactor Physicist Award (American Nuclear Society, 2023)
• Most Cited Paper in Progress in Nuclear Energy (2016)
• Best Technical Paper in Progress in Nuclear Energy (2013)

Research Contributions His publications emphasize reactor safety analysis (e.g., PCMI effects, NECTAR benchmarking) and fusion chamber dynamics. Fiorina has led collaborations on open-source tools like GeN-ROM for molten salt reactors and contributed to international initiatives like IAEA's fast reactor thermal-hydraulics studies. His recent work explores AI's role in nuclear engineering, including surrogate modeling for transient simulations.

Labs/Teams Fiorina directs the Computational Nuclear Engineering Lab at Texas A&M, focusing on multiphysics software development and validation against experimental data from facilities like the CROCUS reactor.