Data-driven Optimization and Control

The group contributes to the following application oriented research topics of WIAS:

Many models in statistical physics contain random paths with interactions of various natures, like polymer models, where the path has a self-repellence and attractive interactions with the surrounding medium, or mass transport models in random medium, where the path carries a random mass that is increased and decreased, depending on the properties of the space visited, or self-intersection properties of the path. Also coupled nonlinear diffusion equations are used for modeling such phenomena. [>> more]

For more than a hundred years diverse processes and phenomena in the natural sciences have been modelled using random particle systems. At the WIAS macroscopic phenomena in such large systems are analyzed with particular focus on phase transitions such as percolation or gelation. [>> more]

Industrial processes are currently experiencing their fourth revolution. The entire production process is connected and equipped with sensor technology, which makes huge amounts of data available. Workers are not only supported by technical visualization and information processing, but parts of the decision-making processes are even carried out independently with the help of AI systems. The large amount of data and the fully automated process pose new challenges for mathematics, but offer unprecedented opportunities for optimization algorithms, not only in the optimization of individual production steps, but across the entire value chain. [>> more]