Research Topics
The chair’s primary research focus is on the development of efficient numerical methods for solving forward and inverse problems involving stochastic differential equations. Specifically, the focus lies on both theoretical and methodological topics, as well as theoretical sound methodologies tailored to target applications.
Current real-world applications range from stochastic modeling (i.e., forecasting and optimization) of power generation, wear degradation, and fouling deposition, to seismic source inversion, fatigue modeling in material sciences, optimal design of electrical impedance tomography experiments, and financial option pricing, to name but a few. Examples of theoretical/methodological topics include hierarchical approximation techniques for forward and inverse uncertainty quantification, stochastic optimal control, and data-driven stochastic modeling.