Stefania Fresca

Stefania Fresca is a researcher at Politecnico di Milano, holding a Researcher academic rank. She specializes in AI, scientific computing, and mathematical modeling with applications in cardiac electrophysiology. Her work focuses on developing deep learning-based reduced order models (DL-ROM) for complex systems like cardiac action potential simulations. She has contributed to publications in prestigious journals such as PLoS ONE and Computer Methods in Applied Mechanics and Engineering. Her methodologies improve computational efficiency for parametrized PDEs, impacting both industrial design and clinical decision-making in heart dysfunction analysis. She has also interned at Ernst & Young in risk advisory roles.

• Education: Mathematical Models and Methods (2017-2021), Mathematical Engineering (2014-2017) at Politecnico di Milano

Research interests include: AI-driven model reduction, HPC applications, and biomedical modeling. Her DL-ROM framework outperforms traditional projection-based methods in electrophysiology simulations. She actively publishes in top journals and collaborates on grants related to parametrized systems.