In spring 2020, new projects will start in the Technomathematics group of Prof. Dr. Dr. hc Peter Maaß, who in cooperation with the industrial partners EWE, Siemens, Engineering System International, Deutsche Bahn, Bruker Daltonik, Proteopath, ProCon X-Ray, atacama blooms and Volkswagen combine basic research on AI with industrial applicability. A key point of research are invertible network architectures that allow the results to be interpreted directly in the respective specialist discipline. Now, however, the employees at ZeTeM have a particular problem: There are not enough qualified candidates for research in this area. In the medium term, the planned realignment of the technical mathematics course towards industrial mathematics and data analysis should help.

The digital award ceremony took place on 16 March, you can find more information here. The award winners of the last years can be found here.

Louisa continues her research work in our working group within the Helmholtz School for Marine Data Science with the PhD project "MarDATA - Monitoring a stressed ice shelf - Machine learning algorithms to detect icequakes in 20 years of seismological records at Neumayer station, antarctica" in cooperation with the Alfred Wegener Institute.

In preparation for her PhD in the MarDATA Helmholtz School for Marine Data Science in cooperation with the University of Bremen, the AWI in Bremerhaven, the GEOMAR in Kiel and the Christian-Albrechts-University Kiel, Louisa Kinzel developed and tested machine learning models in her master's thesis at ZeTeM to automate the process of earthquake analyses.

In December/January, the research ship Polarstern brought the researchers and the wintering crew to Neumayer Station. The two scientists Timo Dornhöfer and Lorenz Marten, who are responsible for the geophysical observatory, are now working on implementing the newly developed models on site and testing them during operation to support them in their routine task of earthquake picking.

So the ZeTeM has now reached into the eternal ice of Antarctica with its novel developments in machine learning!

In the keynote lecture of the Challenge Workshop, Prof. Wil Schilders from the University of Eindhoven gave a far-reaching insight into real and artificial intelligence (AI) for science and engineering. Afterwards, the participants had the chance to learn how Siemens, Deutsche Bahn and EWE integrate the challenge and opportunity of artificial intelligence into their research and development processes. In addition, the latest scientific results on stochastic and data-based models for electricity demand and on modelling of turbulent flows by generative learning were presented in two scientific lectures.

In the training course, an introduction to training neural networks with PyTorch was given, model-based classical approaches (ISTA) and data-based methods (LISTA) as well as their combination were covered. The programming tasks for the participants, who were mainly connected online, came from a real application scenario from computed tomography.

We would like to thank all speakers for their contributions here in Bremen and hope that all participants, whether in person or online, took away new ideas and suggestions from the event.

You can find more information here.