معرفی
Stefania Fresca is an Assistant Professor in Numerical Analysis at the MOX Laboratory (Modeling and Scientific Computing) within the Department of Mathematics at Politecnico di Milano, Italy. She is part of the Future Artificial Intelligence Research (FAIR) Project. Previously, she held a postdoctoral position at MOX and conducted research at the University of Cambridge as a Visiting Researcher (2023–present) and during a visit to the Isaac Newton Institute (March–April 2023).
Her research focuses on scientific machine learning, reduced order modeling (ROM), and numerical approximation of PDEs, with applications in engineering, biomechanics, and fluid dynamics. She develops deep learning-based ROM frameworks to accelerate simulations of complex systems, emphasizing theoretical foundations and practical efficiency.
Education: PhD in Mathematical Models and Methods in Engineering (2021, Politecnico di Milano), MSc in Mathematical Engineering (2017, Politecnico di Milano & Sorbonne Universités), BSc in Mathematical Engineering (2014, Politecnico di Milano).
She has organized multiple mini-symposia at conferences like ECCOMAS 2024 and SIAM UQ24, focusing on deep learning and ROM interactions. Upcoming engagements include a lecture at the Data-Driven & Reduced Order Models in Biomechanics Summer School (April 2025).
Her work bridges theoretical advancements in neural networks and practical applications, addressing challenges in computational efficiency and model interpretability.
