Stefano Pagani
Associate Professor
Milan, Lombardy, Italy
Summary
👤
Senior🎓
Top SchoolStefano Pagani is an Associate Professor and computational mathematician with eight years of research-focused experience developing multiscale, multiphysics models for biomedical applications. He specializes in integrating clinical data into patient-specific simulations and creating scientific machine learning approaches that marry physics-based models with neural networks to improve prediction and generalization. His work emphasizes efficient reduced-order solvers and machine-learning techniques for uncertainty quantification, translating advanced numerical methods into practical tools for clinical decision support. Trained at Politecnico di Milano (PhD, cum laude), he has progressed from PhD student to faculty at the same institution with postdoctoral experience at EPFL, reflecting both deep theory and collaborative, multidisciplinary practice. An understated strength is his focus on tractable, computationally efficient methods—making complex cardiac and biomedical inverse problems solvable in realistic settings.
8 years of coding experience
8 years of employment as a software developer
Doctor of Philosophy (Ph.D.), Mathematical Models and Methods in Engineering, cum Laude, Doctor of Philosophy (Ph.D.), Mathematical Models and Methods in Engineering, cum Laude at Politecnico di Milano
Italian, English
Github Skills (1)
matlab2
Programming languages (2)
Github contributions (5)
StefanoPagani/LocalROM
May 2018 - Dec 2018
Contributions:18 commits, 8 pushes, 1 branch in 7 months
StefanoPagani/StefanoPagani.github.io
Apr 2018 - Jan 2019
Contributions:22 pushes, 1 branch in 9 months
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