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Published:
New preprint: A Certified Goal-Oriented A Posteriori Defeaturing Error Estimator for Elliptic PDEs
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Excited to give a talk on analysis-aware defeaturing at IGA 2025 in Eindhoven.
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Happy to give a talk on analysis-aware defeaturing at ENUMATH 2025 in Heidelberg.
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New preprint: Analysis-Aware Defeaturing of Dirichlet Features
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New preprint: Extension Operators for Fractional Sobolev Spaces on Lipschitz Submanifolds
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Looking forward to give a talk on analysis-aware defeaturing at the Swiss Numerics Day 2025 in Basel.
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Happy to contribute to the 13th Functional Imaging and Modeling of the Heart International Conference, June 1 - 5, Dallas USA, together with HernĂ¡n G. Morales.
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Excited to join the EPFL PhD Excellence Program to complement my PhD training!
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New preprint: Nonlinear model reduction with Neural Galerkin schemes on quadratic manifolds
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Looking forward to participating in the IGA Autumn School organized by the CREATOR team at TU Darmstadt
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Happy to participate in the Lake Como Summer School on Isogeometric Analysis
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Happy to give a talk at the 16th International Conference on Mathematical and Numerical Aspects of Wave Propagation in Berlin
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New preprint: Galerkin Neural Network-POD for Acoustic and Electromagnetic Wave Propagation
Short description of portfolio item number 1
Short description of portfolio item number 2 
Preprint in arXiv, 2025
Preprint in arXiv, 2025
Preprint in arXiv, 2025
Published in MathematicS In Action, 2022
Published in Functional Imaging and Modeling of the Heart, 2025
Published in Journal of Computational Physics, 2025
Published in Advances in Computational Mathematics, 2025
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Talk on the POD-NN method for wave propagation in parameterized domains based on this preprint. The abstract of the talk can be found here.
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Talk on analysis-aware defeaturing of Dirichlet features in Poisson problems, including goal-oriented estimates. The abstract of the talk can be found here.
Published:
Geometry simplification, also known as defeaturing, is crucial for industrial simulations. It not only simplifies the meshing process but also reduces the computational costs of subsequent simulations by decreasing the number of degrees of freedom. Traditional defeaturing methods often rely on geometric criteria alone, overlooking the underlying physics of the problem. In contrast, analysis-aware defeaturing employs a posteriori error estimation, combining the defeatured simulation outputs with the exact geometry information to better inform the defeaturing process.
Published:
Talk on certified a posteriori defeaturing error estimation, including goal-oriented estimates and features subject to Dirichlet boundary conditions.
Teaching assistant, ETHZ, D-MATH, 2019
Teaching assistant, ETHZ, D-MATH, 2020
Main teaching assistant, EPFL, Institute of Mathematics, 2024
Main teaching assistant, EPFL, Institute of Mathematics, 2025