This research seminar explores current topics in stochastic analysis and its interactions with the sciences. It is aimed at advanced master’s students, PhD students, and postdoctoral researchers who are interested in active research directions at the interface of probability, analysis, and scientific modelling.

The seminar focuses on stochastic partial differential equations, stochastic dynamics and random dynamical systems, interacting particle systems, conservative SPDEs, stochastic fluid dynamics, and the effects of noise such as regularization, stabilization, and synchronization by noise. Connections to machine learning, large-scale stochastic systems, diffusion models, and reinforcement learning are also discussed.

Participants will study and present selected research papers, with emphasis on both the mathematical methods and the scientific motivations behind them. The seminar is intended as a research-oriented forum for discussing recent developments, open problems, and techniques in stochastic analysis and its applications.

Programme