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

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 .

The Team

Publications

Contact

Math News

06-27-2023

SIAM Conference on Mathematical & Computational Issues in the Geosciences

The study of geophysical systems at all scales, whether from a scientific or technological perspective, calls for sophisticated mathematical modeling, efficient computational methods, and pervasive integration with data. This effort is fundamentally interdisciplinary. This conference, which took place from 19-22 June in Bergen, Norway, aims to stimulate the exchange of ideas among geoscientific modelers, applied mathematicians, engineers, and other scientists, having special interests in flow in porous media and geophysics.

From MIDS, Prof. Nadja Ray and Dr. Raphael Schulz participated in the conference. They organized the minisymposium "MS7 Multiscale Modeling of Porous Media Applications" and presented in the following minisymposium: "MS41 Mathematical Modeling, Analysis and Simulation of Processes Involving Moving Interfaces" - Part II of II on "Micro-Macro Models for Mineral Dissolution".

You can read the complete conference program HERE.

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.