In 2025, Professor Gianluigi Rozza received the FIS (Fondo Italiano per la Scienza) grant for the ROSA project.

Italian “comunicato stampa” here: https://www.sissa.it/it/news/oltre-5-milioni-di-euro-alla-sissa-dal-fondo-italiano-scienza.

The ROSA – Reduced Order and Surrogate Methods for Advanced Applications project, which will be developed at SISSA mathLab of the Scuola Internazionale Superiore di Studi Avanzati (SISSA), aims to advance surrogate modeling and reduced order methodologies to enable fast, reliable, and scalable simulations of complex physical systems.

While High Performance Computing (HPC) has made it possible to tackle highly sophisticated multiphysics and multiscale problems, many real-world applications still require rapid evaluations, real-time predictions, and deployment on low-power devices. ROSA addresses this gap by developing innovative hybrid approaches that combine data-driven techniques with physics-based modeling, ensuring both computational efficiency and physical consistency.

The project focuses on overcoming key challenges such as limited or noisy data, preservation of fundamental physical properties, and robust uncertainty quantification. By integrating artificial intelligence, generative modeling, and structure-preserving methods within a rigorous mathematical framework, ROSA aims to deliver trustworthy surrogate models capable of supporting advanced applications in engineering, environmental sciences, and biomedicine.

Ultimately, the project contributes to the development of next-generation digital twins and sustainable computational technologies, strengthening European excellence in scientific computing and mathematical innovation.