My general research interests are scientific computing, computational (plasma) physics and more recently also machine learning.

I have developed both particle-in-cell and plasma fluid codes for the simulation of electric discharges (non-thermal plasmas). I'm also active in the development of MPI-AMRVAC, a framework for (magneto)hydrodynamics simulations. My work has focused on topics such as adaptive mesh refinement (AMR) and fast elliptic solvers (e.g., multigrid). I like to study systems that have some intrinsic complexity, not coming from boundary conditions or input data.

Since 2018, I have been working on machine learning methods applied to space weather applications, in collaboration with Enrico Camporeale, as I have taken over two EU projects in this direction from Enrico (AIDA and ESCAPE, see below). Current research focuses on forecasting time-series data, recognizing magnetic reconnection, and the use of unsupervised methods for e.g. dimensionality reduction and clustering.

• 2024-2026 AGILE: Astrophysics on GPUs for InterdiscipLinary Exascience challenges
  Collaboration with O. Porth (PI, UvA) and others, funded by Netherlands eScience Center.
  Total budget: 228 k€, mostly for paying eScience staff working on the project.
• 2023-2029 REGENERATE: Reliable Next Generation Actuation Systems
  NWO KIC project, collaboration with TU Eindhoven, TU Delft and industry partners.
  Total budget: 3.36 M€. CWI got one PhD position.
• 2024-2028 Green Sparks
  TTW OTP project #20344, in collaboration with TU Eindhoven and industry partners.
  Total budget: 1.25 M€. CWI got a PhD position and an 20 month postdoc position.
• 2019-2024 Plasma for Plants
  TTW OTP project #17183, in collaboration with TU Eindhoven and industry partners.
  Total budget: 775 k€. CWI got an 24 month postdoc position.
• 2018-2022 Plasma assisted combustion
  TTW OTP project #16480 in collaboration with TU Eindhoven and industry partners
  Total budget: 903 k€. CWI got 1.5 postdoc years.
• 2017-2022 Let CO2 spark!
  TTW OTP project #15052, in collaboration with TU Eindhoven and industry partners.
  Total budget: 975 k€. CWI got funding for one PhD position and a 24 month postdoc position.
• 2018-2022 AIDA
  EU H2020 project #776262, in collaboration with KU Leuven and other partners.
  Total budget: 1.5 M€. CWI got 219 k€.
• 2019-2023 ESCAPE
  EU H2020 project #824064, large collaboration between European research organizations.
  Total budget: 16.0 M€. CWI got a 24 months postdoc position.

Past postdocs, PhD students etc. in italic

• Alejandro Malagón-Romero
• Ajay Tiwari (In collaboration with Enrico Camporeale)
• Andong Hu (In collaboration with Enrico Camporeale)

I (co-)supervise(d) the following PhD students together with Ute Ebert:

• Yuting Gao (daily supervisor)
• Thom Smits

• Hemaditya Malla (daily supervisor)
• Dennis Bouwman
• Baohong Guo (daily supervisor)
• Xiaoran Li (daily supervisor)
• Zhen Wang (daily supervisor)
• Andy Martinez

• Yihao Guo (2025, TU Eindhoven)
• Hemaditya Malla (2024, TU Eindhoven)
• Baohong Guo (2023, TU Eindhoven)
• Zhen Wang (2023, TU Eindhoven)
• Dennis Bouwman (2023, TU Eindhoven)
• Xiaoran Li (2023, TU Eindhoven)
• Hani Francisco (2023, TU Eindhoven)
• Brecht Laperre (2022, KU Leuven)
• Andy Martinez (2022, TU Eindhoven)
• Alejandro Malagon (2021, University of Granada)
• Shahriar Mirpour (2021, TU Eindhoven, co-promotor)

• Francesca Schiavello (2021, UvA MSc)
• Chris van der Heijden (2021, TU/e BSc)
• Stijn van Deutekom (2020, TU/e BSc)

Examples of research/project ideas:

• Simulating incompressible flow with the Afivo framework
• Exploring hybrid OpenMP/MPI parallelization for AMR frameworks
• Solving plasma fluid equations implicitly. In particular, what is a good preconditioner?
• Improving the convergence rate of Monte Carlo particle swarm simulations in low electric fields. One idea is to limit the drift in electron momentum due to collisions.
• Coupling explicit and implicit time integration for plasma fluid models
• Performing large scale 3D simulations of sprite formation
• Coupling particle and fluid models in energy space, for the study of runaway electron production in electric discharges.
• Extending the discharge model comparison of this paper to other fluid models