The group's main focus is on the application driven development of optimization methods, the close connection to machine learning, and an efficient implementation on computers. Main technologies and fields of expertise comprise nonlinear and integer optimization, as well as optimal control. A specialization is in numerical algorithms for mixed-integer optimization with differential equations. Most of our mathematical models arise from applications in clinical decision support, energy, and mobility. Within the Max Planck research group Mathematical Optimization and Machine Learning we are particularly interested in mathematical methods for a better understanding of a green carbon based sustainable society based on a circular chemical production, compare also the press release related to the nomination of Sebastian as a Max Planck Fellow on October 1, 2023.

Our research has been receiving funding from an ERC consolidator grant, the DFG Research Training Group 2297 Mathematical Complexity Reduction, the EU-supported Excellence Programme of Sachsen-Anhalt, the IMPRS Advanced Methods in Process and Systems Engineering and several DFG, BMBF, and industry projects.