Ionut-Gabriel Farcas

Mathematical modeling and simulation are indispensable tools for understanding the natural world, empowering us to make informed decisions and drive innovation across diverse fields. Two contemporary examples are from aerospace propulsion where rotating detonation rocket engine simulations are used in support of the design of next-generation rocket engines, and fusion plasma physics where simulations are essential for quantifying and predicting turbulent transport in magnetic confinement experiments.

To address these challenges, Dr. Farcaș's research is dedicated to enabling or accelerating predictions and decision-making, and increasing the robustness of numerical models in complex, real-world applications. His work seamlessly blends scientific computing, high-performance computing, and computational physics, with a particular emphasis on scientific machine learning, reduced and surrogate modeling, uncertainty quantification, and sparse grid and multi-fidelity methods.

Beyond research, Dr. Farcaș is passionate about inspiring the next generation of computational scientists through teaching and mentorship.