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

12-21-2023

MIDS wishes you a Merry Christmas

"The real presents are not under the Christmas tree. They sit together in loving company and are grateful for their great happiness together."

With this in mind, the entire MIDS team wishes you and your loved ones a Merry Christmas, peaceful holidays and a Happy New Year.

We also look back with gratitude on an eventful 2023. This year not only brought us a second intake of Data Science students, but also the move to the beautiful, historic Georgianum. We had to wait a long time for the renovation work to be completed, but then we were finally able to move into the impressive premises and celebrate a wonderful opening together with many guests. The institute can finally develop to its full potential and we are already looking forward to everything that may happen in 2024.

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.