“We are very proud that our application convinced the jury – in particular, because we only had a few weeks to prepare in joint collaboration with other universities and higher education institutions. The KU’s scientific focus is rooted in a Christian view of human life. This means that we are committed to a human-centered digital society. The newly approved professorship enables us to intensify our research in this field,” says KU President Prof. Dr. Gabriele Gien. The KU’s success in the competition for these new professorships continues a long line of recently achieved successes: In fall this year, the KU will establish an Institute of Applied Mathematics, Machine Learning and Data Science at its Ingolstadt campus. The city of Ingolstadt supports the establishment of the institute by financing three endowed chairs over a period of five years. Already in fall last year, the KU had been successful in acquiring as much as seven tenure track professorships in the context of the joint federal states and government program for promoting young researchers. The first part of those tenure track professorships are already open for applications and will be assigned to the successful candidates in the near future. Furthermore, the KU has established a close collaboration with the Technische Hochschule Ingolstadt and other partners from the regional industry and economy for setting up the new Ingolstadt-based center “Artificial Intelligence Network Ingolstadt gGmbH” (AININ).
The KU’s successful application for the present competition was submitted in collaboration with other partners for the interdisciplinary topic area “Resource Aware Artificial Intelligence for Future Technologies” and closely interlinks concepts for several professorships. Besides the KU, other collaboration partners are, for example, the Friedrich Alexander University Erlangen-Nuremberg, the Technical University of Munich (TUM) and the University of Bayreuth. The central topic of the newly approved “Professorship of Mathematics – Reliable Machine Learning” is the reliability of so-called neural networks that are for example used in automatic image processing or medical diagnostics. While there are already outstanding results in the practical application of AI, these are not yet explainable and secured by mathematical-analytical fundamental research. At the same time, we are currently witnessing growing demands with regards to performance, safety and sustainability of AI applications as well as regarding ethical and legal safety. In close collaboration with researchers and companies in the area of robotics, medical technology and mobility, the collaboration of universities seeks to promote the development of novelty procedures that allow application in diverse ways, ensuring that performance is high enough to produce correct and robust results despite limited resources. The aim of the professorship is to work towards guaranteed success of the neural networks of the future. Research seeks to ensure that the application of such networks in future will neither need huge amounts of training data to support them in their learning processes nor have an unnecessarily high energy consumption.