Data-Driven Computational Science
Presentation
We are a group of applied mathematicians excited about the interplay between Partial Differential Equations (PDEs) and data. We make both topics "sing together" to build algorithms to assist in decision processes.
Our methods are interpretable and come with mathematical guarantees on their reliability.
Here is a short, visual presentation of what we do, and here are some topics that we study:
- Approximation and Learning: model reduction, neural networks, tensor methods
- Inverse Problems and Data Assimilation: optimal reconstruction schemes, sensor placement
- Numerical Optimal Transport
- Numerical Analysis of PDEs: kinetic models, gradient flows, pedestrian and particle dynamics, a posteriori error estimation, domain decomposition.
- Applications: pedestrian dynamics, haemodynamics, pollution, epidemiology, nuclear physics (fusion and fission processes)
Team Members
Where to find us
- The core of the group is based at TU Eindhoven
- We belong to its Mathematics & Computer Science Department
- More specifically, we are embedded in CASA, the Center for Analysis, Scientific Computing and Applications