Since April 2022, I have been a university assistant and post-doctoral researcher at the University of Vienna in the “Numerics of PDEs” group, with Prof. Ilaria Perugia. My main interests here are the development and analysis of model order reduction algorithms for the surrogate modeling of parametric time- and frequency-domain wave-propagation applications, and, more generally, the numerical modeling and approximation of such problems.

Before that, I was a post-doctoral researcher at EPF Lausanne in the “Scientific Computing and Uncertainty Quantification” (CSQI) group, with Prof. Fabio Nobile.

I was awarded my PhD title in Mathematics at EPF Lausanne in December 2021. My PhD work under the supervision of Prof. Fabio Nobile is summarized in my thesis, titled “Model order reduction based on functional rational approximants for parametric PDEs with meromorphic structure” (available here). Before that, I got my Master’s degree at EPF Lausanne, with a thesis on “Randomized low-rank approximation of matrices and tensors” (available here), under the supervision of Prof. Daniel Kressner.

I have also contributed to the organization of the model order reduction summer school 2020, a virtual event hosted at EPFL with the objective of disseminating knowledge on model order reduction.

I love teaching, and I find it especially rewarding to help students discover the “truth” hidden behind the printed words on the textbook.

## Research interests

My research interests lie at the intersection of:

• model order reduction (non-intrusive surrogate modeling of parametric problems)

• approximation theory (rational and non-smooth approximation)

• numerical discretization of PDEs (finite elements, boundary elements, virtual elements)

• wave-propagation applications (wave, Maxwell, and Helmholtz equation, scattering problems)

• scientific computing (high-performance and parallel programming)

Being an applied computational mathematician, my research work so far has been characterized by a balance between theory (possibility of approximation, convergence, stability) and applications (optimal design problems in electrical and mechanical engineering, simulation of wave propagation). In all of this, I have strived for algorithmic efficiency and open-source coding: see here for the open-source MOR library RROMPy that I have developed during my PhD and here for some of my open-source contributions on ZENODO.