Dynamical Systems

Modern key technologies in science and technology require modeling, simulation, optimization, or control (MSO) of complex dynamical systems. Most real-world systems are multi-physics systems, combining components from different physical domains and with different accuracies and scales in the components. Our group, which was established in Nov. 2020, is working on a wide range of research topics for complex dynamical systems, ranging from the analysis and design of efficient surrogate modeling techniques, numerical implementation details, and modeling aspects. Currently, we address research questions related to

• port-Hamiltonian systems,
• model-order reduction and system identification,
• certified machine learning, and
• delay differential-algebraic equations.

If you are a scientist who wants to collaborate with us or a student who wants to write their thesis on topics related to dynamical systems, please reach out to us.