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University of Bayreuth granted three new professorships for artificial intelligence

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University of Bayreuth, Press release No. 077/2020, 15 May 2020

The University of Bayreuth will install three new professorships in the field of artificial intelligence. This was announced in Munich today by Bavaria's Minister of Science, Bernd Sibler. With applications in the fields of energy management, machine learning, and materials research, the University of Bayreuth was one of the winners in the competition among Bavaria’s universities and colleges for a total of 50 new AI professorships. The expansion of research and teaching in the field of artificial intelligence is a focal point of the Bavarian High-Tech Agenda announced by Premier Dr. Markus Söder in October 2019.


"The decision of the Bavarian State Government to establish three new professorships for Artificial Intelligence at the University of Bayreuth is a milestone for the strategic development of our university in a central field of the future. At the same time, it provides fresh momentum to intra-Bavarian cooperation between universities and universities of applied sciences. Although the new AI professorships in Bayreuth are located in different faculties, through professional cross-links, they will strengthen the interdisciplinary networking on our campus significantly. This gratifying success would not have been possible without the dedicated cooperation of many members of our university in preparing the applications for funding. My sincere thanks go to all those involved - and especially to those researchers whose applications were not accepted today. Nevertheless, the ideas and projects these contain will remain valuable starting points for the ongoing development of the University of Bayreuth in this important field", explained University President Prof. Dr. Stefan Leible after the announcement of the decision today.

From basic research to technology-related projects

"Artificial intelligence is increasingly proving to be a key driver of innovation for the 21st century. The University of Bayreuth therefore welcomes the courageous decision of the Bavarian State Government in making such a comprehensive and long-term investment into research and development in this field. Our new AI professorships are a significant boost to the innovative dynamic already prevailing at the University of Bayreuth. With their specialist focal points, they cover a broad range of territory, from basic research of a theoretical nature, to the technological application of AI in the natural sciences. As a result, the professorships have great potential for joint research and development work with companies, but also for the foundation of start-ups, which we specifically support in Bayreuth", says Prof. Dr. Torsten Eymann, vice president of the University of Bayreuth in the area of digitalization and innovation.

Intelligent energy management

A new professorship for Intelligent Energy Management will deal with the basic research into and application of artificial intelligence in the field of electrical energy supply and electrical energy networks. One focus will be on decentralized energy systems in which renewable energy sources such as the sun and wind play a major role. Numerous different players and business models come together in these highly complex systems. Consequently, a large amount of contradictory information and uncertain forecasts must be processed on a regular basis. The development of new AI methods is therefore the focus of the professorship. Ideally, they will enable better predictions of energy production and demand, of available storage capacities, and of grid bottlenecks, but also serve to better control and regulate the overall system. Intelligent energy management includes the use of power plants, the charge management of stationary storage facilities, and electric vehicles.

In this way, the professorship will be able to make an important contribution to the reliable supply of renewable energy. It is integrated into the focus area of "Energy Research and Energy Technology" of the University of Bayreuth. On the Bayreuth campus, it will cooperate closely with the Centre for Energy Technology (ZET), the Bavarian Centre for Battery Technology (BayBatt), and the Fraunhofer FIT project group Information Systems Management. The successful application for the professorship was supported by the University of Bamberg and the Universities of Applied Sciences in Hof and Munich. Apart from the application by TH Rosenheim for AI-based energy data analysis, it was the only application in the field of energy technology that was successful in the AI competition of Bavaria’s universities and colleges.

Machine learning

"Data-driven dynamic optimization and control" is the remit of another new AI professorship. This is a technological problem that many companies, research institutes, and administrative bodies are keen to solve. Traditional machine learning methods often require more IT capacity than is available on mobile systems, which have to react to new situations in real time. The new professorship will work towards overcoming this problem in research and development. It is located at the interface of mathematics, computer science, and robotics. The aim is to combine machine learning techniques with methods of optimal control and regulation in such a way that they can be used even in mobile systems. There will be a multitude of fields of application for the research results. These include the development of autonomous vehicles, the use of robots in medicine, and efficient, environmentally friendly technologies (CleanTech). Cooperation with energy research at the University of Bayreuth is therefore also planned, in particular with the Bavarian Centre for Battery Technology (BayBatt). The professorship is also part of a network of new AI professorships, in which TU Munich, FAU Erlangen-Nuremberg, and the Catholic University of Eichstätt-Ingolstadt are also involved.

Sustainable materials

Materials research and development are of central importance for the scientific profile of the University of Bayreuth. It extends to the focus areas of "Polymer and Colloid Research", "New Materials", and "Energy Research and Energy Technology". A new AI professorship in the field of physicochemical materials analysis will open up new possibilities for artificial intelligence in this interdisciplinary field of research. An important goal is to gain a deeper understanding of the relationships between the structures and properties of materials. However, because measurement data in materials research are often very diverse and complex, new computer-based methods must be developed and tested for their evaluation.

The new professorship is to be positioned at the interface between experimental materials research and computer-aided analysis. This will allow analyses of the structures and properties of the latest materials to be carried out more quickly, more precisely, and more thoroughly. Valuable insights are expected, especially in the areas of time-resolved scattering techniques, microscopy and spectroscopy. In all three areas, the University of Bayreuth has high-performance research technologies at its disposal, which are networked in a way that is unique in Germany. This enables comprehensive material analyses on a wide variety of spatial and time scales, but at the same time places very high demands on the scientific understanding of the data obtained. Hence, with the help of artificial intelligence, significant progress will be made in the development of materials needed for the sustainable technologies of the future. The Bayreuth junior professorship is part of a network in which a new AI professorship at Coburg University of Applied Sciences is also involved.

Further information

on the new AI professorships at Bavarian universities and colleges is contained in today's press release from the Bavarian State Ministry of Science and the Arts:


Prof. Dr. Torsten Eymann
Vice President for Digitalisation & Innovation of the University of Bayreuth
Chair of Information Systems Management
Fraunhofer project group Information Systems Management of Fraunhofer FIT
University of Bayreuth, 95440 Bayreuth
Phone: +49 (0)921 55-7660
E-Mail: Torsten.Eymann@uni-bayreuth.de

Editorial office:

Christian Wißler
Science Communication
University of Bayreuth
Phone: +49 (0)921 / 55-5356
E-mail: christian.wissler@uni-bayreuth.de


Ralph Reindler

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