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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Math News

05-15-2024

Young mathematical elite

The last few weeks have been a hive of activity at MIDS. In addition to the Open Day and Girls' Day, on which we welcomed interested pupils to the Georgianum, two special groups also visited us recently.

On 24.04.2024, a group of pupils from a German school in Prague visited MIDS. Having previously explored the WFI, the students were warmly welcomed at the Georgianum. Dr. Raphael Schulz introduced the MIDS and the Data Science course. Finally, the students were able to learn about the page rank algorithm in a taster lecture.

On 03.05.2024, we then welcomed a group of highly talented students from the region to the institute. Prof. Nadja Ray explained the concept of studying with a lecture/exercise as opposed to school. They then took part in the lecture "Analysis II for Data Science". The topic of convergence of sequences was discussed. At the end of the visit, Prof. Felix Voigtlaender gave a lecture on the topic "What is machine learning?"

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.