Research topics

The main focus of the Stochastic Processes group is the study of stochastic (partial) differential equations and their applications. The group studies evolution problems and dynamical systems with random parameters, integral-differential Volterra equations, stochastic Schrödinger equations, stochastic Navier-Stokes and Euler equations, and interacting particle systems. The methods used include Malliavin calculus, Feynman path integration, dyadic models and rough path integration.
Applications include neuroscience, networks, finance, quantum mechanics, materials with memory, fluid-dynamics, data assimilation, parametric statistics, machine learning, reinforcement learning, lithium-ion batteries.