Welcome to the page of the Professorship for Data Assimilation

In order to be able to predict severe weather events or the melting of ice in the Arctic, information in the form of heterogeneous data must be linked with numerical models of dynamic systems. This is done through data assimilation, which makes it possible to better investigate processes and predict their further development. In the field of data assimilation, the professorship is concerned with the further development of data science algorithms by incorporating physical conservation laws, and solving correspondingly large optimisation problems in the environmental sciences. Quantifying the uncertainties of predictions, numerical models and observations also plays a central role here.

About us

Prof. Janjic introduces herself and the chair

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The Team

Publications

Contact

Math News

05-04-2026

New PhD Researcher at the Chair of Analysis: Welcome, Anna Simon

On 1 May 2026, Anna Simon joins the team at the Chair of Analysis. After successfully completing her Master’s degree in Mathematics at the University of Regensburg, she is now beginning her PhD at KU.

Her research focuses on developing new analytical approaches to precisely describe the effective behaviour of thin elastic structures with fine-scale, periodic reinforcements. These questions are motivated by concrete applications in medical technology. Her PhD project is part of the collaborative initiative “MAS-TOB: Multiscale Analysis and Structural Optimisation of Patient-Specific Therapeutic Orthoses and Bandages”, conducted jointly with the RPTU Kaiserslautern-Landau and the Fraunhofer Institute for Industrial Mathematics ITWM, and funded by the Federal Ministry of Research, Technology and Space (BMFTR).

A warm welcome to Eichstätt, Anna - we very much look forward to working with you!

MIDS seminar

Mathematical Institute for Machine Learning and Data Science

The Heisenberg professorship is part of the Mathematical Institute for Machine Learning and Data Science, MIDS.
Learn more about MIDS here.