Andrea Scaglioni

Andrea Scaglioni is a Postdoctoral Researcher in computational mathematics at the University of Vienna since October 2024, working under Professor Ilaria Perugia. He received his Ph.D. from the Technical University of Vienna (TU Wien) in October 2024, focusing on stochastic dynamics in micromagnetic systems, and holds a Master's degree in Computational Science and Engineering from EPFL (Switzerland, 2019).

His academic background includes:

• Ph.D. in Computational Mathematics, Technical University of Vienna (TU Wien), 2024
• Master's in Computational Science and Engineering, EPFL, Switzerland, 2019

Scaglioni specializes in Uncertainty Quantification for Partial Differential Equations using high-dimensional interpolation methods like Sparse Grid Interpolation to construct surrogate models. His research targets stochastic micromagnetics, particularly the Landau-Lifshitz-Gilbert equation, with applications in modeling magnetic hysteresis phenomena. He actively contributes to Austria's numerical analysis community through conferences and collaborations within Prof. Perugia's research group.

His recent presentations include talks at the Annual ÖMG-DMV Meeting (Linz, September 2025), the International Symposium on Hysteresis Modeling and Micromagnetics (Torino, May 2025), and workshops on stochastic PDEs at TU Wien (September 2024). These highlight his focus on surrogate modeling, reduced-order methods, and sparse grid techniques for stochastic dynamics in magnetic systems.