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Since August 2025, I am an Assistant Professor at Stockholm University in the Research Group of Computational Mathematics, working on model order reduction methods for complex parametric problems. Since 2024, I have also served as chair of the Numerical Analysis Seminar Series.

Before that, I was a postdoctoral researcher at KTH and the University of Vienna, working with Prof. Sara Zahedi and Prof. Ilaria Perugia on numerical methods for parametric PDEs, wave propagation, and multiphase flow.

I completed my PhD at EPFL in 2021 under the supervision of Prof. Fabio Nobile.

More about me

I earned my PhD in Mathematics from EPFL in December 2021, under the supervision of Prof. Fabio Nobile, in the “Scientific Computing and Uncertainty Quantification” (CSQI) group. My thesis, titled Model order reduction based on functional rational approximants for parametric PDEs with meromorphic structure, is available here. Prior to that, I completed my Master’s degree at EPFL with a thesis on Randomized low-rank approximation of matrices and tensors (link), supervised by Prof. Daniel Kressner.

During my time at EPFL, I was also involved in scientific outreach and organization, including the Model Order Reduction Summer School 2020, a virtual event aimed at promoting advanced techniques in model order reduction.

After my PhD, I held a postdoctoral and university assistant position at the University of Vienna in the “Numerics of PDEs” group led by Prof. Ilaria Perugia. After staying in Vienna for about two years, I became a postdoctoral researcher at KTH Royal Institute of Technology in the Section of Numerical Mathematics, working with Prof. Sara Zahedi between February 2024 and July 2025. My primary research interests there included surrogate modeling for parametric multiphase flows via model order reduction.

Since October 2024, I have served as chair of the Numerical Analysis Seminar Series at KTH. In 2025, I also contributed to organizing career development initiatives for PhD students and postdocs in mathematics at KTH.

Since August 2025, I have been an assistant professor at Stockholm University, in the Research Group of Computational Mathematics. My research continues to focus on the development and analysis of model order reduction techniques for complex parametric problems.

As a teacher, my goal is to empower students to become active learners, capable of critically engaging with material and uncovering the truths that lie beyond the printed page.

Research interests

My research lies at the intersection of several areas in applied and computational mathematics:

• Model order reduction, with a focus on non-intrusive surrogate modeling for parametric problems
• Approximation theory, including rational and non-smooth approximation techniques
• Numerical discretization of PDEs, using finite element, boundary element, and virtual element methods
• Wave propagation, particularly for the wave, Maxwell, and Helmholtz equations and related scattering problems
• Scientific computing, with emphasis on high-performance and parallel programming

As an applied computational mathematician, my work aims to balance rigorous theoretical foundations (such as approximation guarantees, convergence analysis, and stability) with practical applications, including optimal design in electrical and mechanical engineering and the simulation of wave phenomena.

Efficiency and reproducibility are central to my approach. I actively develop open-source software: you can find some of my contributions on ZENODO and GitHub, as well as the model order reduction library RROMPy, which I developed during my PhD.