André Schlichting

Research

My research focuses on the qualitative and quantitative analysis of complex dynamical systems arising in physics, chemistry, and engineering. I am particularly interested in understanding how macroscopic behavior emerges from microscopic or stochastic models, using tools from partial differential equations (PDEs), stochastic analysis, and variational methods.

A central theme in my work is the study of metastability and phase transitions in systems motivated by statistical mechanics and particle dynamics. This includes investigating how collective effects and noise lead to rich dynamical phenomena such as nucleation, coarsening, and metastable states. At the interface with stochastic analysis, I analyze many-particle limits of interacting systems and their continuum descriptions, often formulated as gradient flows in spaces of probability measures.

I am also interested in structure-preserving numerical schemes for nonlinear diffusion and aggregation equations, the long-time behavior of dissipative systems via entropy and functional inequalities, and variational convergence methods that connect discrete and continuous dynamics. My research extends to nonlocal and graph-based models, motivated both by physical systems and machine learning, where questions of dimension reduction and multi-scale dynamics naturally arise.

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