Vorträge

This talk will be devoted to several topics in classical and modern control theory. Classical stabilization techniques for linear and nonlinear control systems as well as modern attempts to linearize nonlinear systems will constitute the core for this presentation. In particular, the first part will consist of a brief summary of my Master's Thesis on the foundations of mathematical control theory in finite dimension. During the second part, we will catch a glimpse into modern control theory involving the Koopman operator focussing on advances and difficulties. The third part will be on my current PhD topic "Time-Optimal Control of Linear Systems in Non-Reflexive Banach Spaces". The official introduction to my person will also not come too short.

This talk will start with a high-level overview on how machine learning can be used to improve weather and climate predictions. Afterwards, the talk will provide more detail on recent developments of machine learned weather forecast models and how they compare to conventional models and numerical methods.