[Translate to Englisch:] MIDS Logo

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

Vorschaubild Youtube Tijana

Please note: By clicking on the image area, you give your consent for video content to be reloaded from YouTube, for YouTube/Google cookies to be stored on your IT system and for personal data such as your IP address to be passed on to Google. If you click on another video after having finished watching the video content, YouTube will open in a new tab of your browser and will collect more data from you. Further information is provided in our data protection notice and under Google Privacy .

Math News

Register now for the TRR 165/181 Joint Conference

from March 27-30 and be there when MIDS welcomes two global research communities to KU. Registration deadline is February 26, 2023!

The conference brings together researchers working on consistent modeling, data-driven approaches, and uncertainty in short-to-medium term forecasting with researchers on related questions on climate scales. It aims to interlink recent advances in both fields and showcase new developments the underlying theory, methods, and parametrizations.

Topics will be:

  • uncertainty quantification and predictability
  • parametrizations and structure-preserving and invariant-conserving schemes
  • data-driven modeling and machine learning, data assimilation
  • waves in atmosphere and ocean, wave-vortex interactions

The conference is supported by the German Collaborative Research Networks TRR 165 "Waves to Weather" and TRR 181 "Energy Transfers in Atmosphere and Ocean" funded by the German Research Foundation (DFG). It will feature highlights from within the networks as well as contributions from the global research community.

More information about the program and registration can be found HERE. Registration deadline is February 26!

The conference is organized by the Mathematical Institute for Machine Learning and Data Science (MIDS) of KU. The organizers are Prof. Tijana Janjic, Heisenberg Professor of Data Assimilation and Prof. Marcel Oliver, holder of the Endowed Chair of Applied Mathematics.

Prof. Tijana Janjic
Prof. Marcel Oliver

Mathematical Institute for Machine Learning and Data Science

[Translate to Englisch:] Logo MIDS

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