A series of lectures was launched for the new Elite Graduate Program Scientific Computing at the University of Bayreuth, which is intended to familiarize students with the subject and variety of scientific computing. For the organizers around Prof. Bebendorf, speaker of the program, the scientific exchange was particularly important.
Describing and, above all, solving real problems often requires cooperation from a wide range of disciplines. Scientific computing, as well as the Elite Graduate Program "Scientific Copmputing", adresses the entire solution chain, i.e. the physical description of a problem, the mathematical modeling, numerical algorithms and finally the efficient (parallel) implementation. Thus, it is not remarkable that the field of Scientific Computing has a true variety of different topics and contains methods such as artificial intelligence and machine learning. In the lecture of Prof. Schneider, EAH Jena, the students could learn how to use machine learning in an optimization problem to find the best possible parameters.
A completely different topic was discussed in the lecture of Prof. Steinbach, TU Graz. Prof. Steinbach deals intensively with the new approach of space-time in the discretization of partial differential equations. Here, the usual approach is not to discretise time and space separately, but to understand both as one quantity and to discretise them accordingly as space-time.
Presenting the topic of scientific computing to the students was not the only intention in organizing such a series of lectures. Equally important was the scientific exchange among each other. Some guests like Prof. Praetorius, TU Vienna, or Prof. Bonaventura, Politecnico di Milano, stayed several days to discuss and advance current topics of Scientific Computing until late in the evening.
Text: Maximilian Bauer, Elite Graduate Program "Scientific Computing“
