CEMRACS 2021: Data Assimilation and Model Reduction in High Dimensional Problems
A significant challenge arising in increasingly many modern applications is how to blend complex mathematical models, often based on differential or integral equations, with the large and, possibly, noisy data sets which are now routinely available in many fields of engineering, science and technology. Growing efforts are made to develop a coherent mathematical framework where one of the main obstructions is the high dimensionality of the involved mathematical objects, which requires efficient sampling or optimization techniques for large-scale problems and, possibly, model order reduction strategies. The CEMRACS 2021 will be devoted to this topic of data assimilation and model reduction in high-dimensional problems. It is by nature interdisciplinary, not only by the amount of the different mathematical skills that need to be invoked, but also by the detailed knowledge that each specific application requires.
