Projects and Supervision

Projects

Taming frequency in Bayesian inverse wave scattering, Vidi project
PI, 2026-2031, 850k€, funded by NWO.

UTOPYS: Understanding Large and Complex Power Systems, Large Scale Research Infrastructure Co-PI, 2026-2036, 16.5M€ (Radboud part, with G. Lord, ~240k€), funded by NWO.

Towards a chemical self-organizing computer: Mathematical modeling of Marangoni flows (2023) Co-PI, 2023, 50k€, funded by Radboud Interdisciplinary Research Platform (IRP).

Current PhD students

Jordi de Lange (01/2023-ongoing), sponsored by Alliander, with G. Lord and S. Rieken.
Wouter van Harten (11/2021-ongoing), Numerical Approaches to Uncertainty Quantification for PDEs on Parameterized Domains. Defence date: 20 January 2026.

Former PhD students and Postdocs

Sabrina Schönfeld (PhD student, 05/2019-12/2023), Environmental stress level - a mathematical modeling framework to investigate the influence of the microenvironment on tumor cell survival, with C. Kuttler. Link to PhD thesis.
Julio Careaga (Postdoc, 01/2023-08/2023), with V. Nikolić.

Master students

Janna van Assen (ongoing), with M. Hinne.
Jos Aalberts (2025), Wind Power Forecasting by Applying Gaussian Process Regression, internship with TenneT (team of G. Karaaslan).
Simon Geritz (2025), An A Priori Error Analysis of a Stochastic Collocation Method on the Binwise Averaged Radar Cross Section, internship with NLR (team of H. van der Ven).
Max Hofman (2025), Preconditioner Selection and Placement - Iteratively solving the heat equation in parametric studies for grid management, with W. van Harten, internship with Alliander (team of S. Rieken).
Daan Jansen (2024), Neural Network Approximations of Parametric PDEs.
Safiere Kuijpers (2023), Bayesian Shape Inversion for Scattering Transmission Problems, with W. van Harten. Link to thesis.
Dirk Heldens (2023), Reducing uncertainty in cable temperature estimation, internship with Alliander (team of S. Rieken).
Alexandra Starostina (2020), Robin boundary conditions for PDE-based sampling of Gaussian Random Fields, with B. Wohlmuth.

Bachelor students

Renske Zeppenfeldt (ongoing), internship with Alliander (team of R. Claij).
Emma Burgers (ongoing).
Dieke van der Heijden (2025), Parallel Numerical Linear Algebra.
Janna van Assen (2024), Deep learning as optimal control problem.
Houssam Larhdaf (2024), Stock price forcasting: a Kalman filter approach, with G. Lord.
Laura van Leuven (2022), Gradient descent methods and their use in machine learning, with G. Lord.