Scientific Computing CWI

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Scientific Computing

Centrum Wiskunde & Informatica

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The Scientific Computing group at CWI develops efficient mathematical methods to simulate and predict real-world phenomena with inherent uncertainties. Our two main research themes are scientific machine learning and uncertainty quantification, and the topics within these themes are neural ODEs, closure models for turbulence, reduced-order models, discretization techniques, stochastic parameterizations, generative models, data assimilation.

Our official CWI page with general information can be found here. On the current page, you can find more detailed information such as the software that we develop in the group and other useful information such as the material used in the semester programmes that we organize, in particular the SciML and UQ semester programmes. Note the upcoming semester programme 2025 on Synergies in numerical linear algebra and machine learning!

Please check our GitHub page with group repositories and our software page.

Members ​

Current members: Benjamin Sanderse (group leader), Wouter Edeling (staff), Daan Crommelin (staff), Dimitris Loukrezis (staff), Syver Agdestein (PhD candidate), Toby van Gastelen (PhD candidate), Rik Hoekstra (PhD candidate), Pardeep Kumar (PhD candidate), Marius Kurz (postdoc), Nikolaj Mücke (postdoc), Henrik Rosenberger (PhD candidate), Robin Klein (PhD candidate), Barry Koren (advisor).

SC group at ECCOMAS 2024

Group seminar ​

To receive news and Zoom links for our group seminar, you can contact Wouter Edeling at wouter.edeling@cwi.nl. For more information, see our seminar page.

News ​

Publications ​

Full list of publications can be found at CWI's institutional repository.