Zeiss Funds Machine Learning Development & Its Application

The Carl Zeiss Foundation is supporting the establishment of a center for machine learning at Aalen University in Germany with 2.7 million euros. Machine learning has quickly become a key technology for industrial applications. The goal is to teach machines how to perform complex tasks intelligently and automatically. By anchoring the topic in studies and further training, the center should secure the need for adequately trained employees.

Already in January, Aalen University of Applied Sciences received funding as part of the pilot program “Joint Professorships at Universities for Applied Sciences” of the Carl Zeiss Foundation. Funding is provided by funding two professorships with six staff positions over a period of five years. The professorships work both at the university and in a company. In this way you can get to know both worlds in an early career phase and combine them. “Many universities today are in competition with business in their search for highly qualified workers in the scientific and technical fields because the same skilled workers are scarce there. That is why new ways are needed. We want to test such an idea together with the Aalen University of Applied Sciences,” says Minister Theresia Bauer, Chair of the Foundation Administration of the Carl Zeiss Foundation.

Aalen University of Applied Sciences uses the funding of the two endowed professorships as the core for setting up a long-planned center for machine learning and its application in industry. The two endowed professorships, called Computer Vision and Deep Learning, are designed to develop modern methods for evaluating image and video data in industrial production.

Aalen University has been strategically expanding its activities in the areas of digitization, Industry 4.0 and machine learning for years. This takes place, for example, through the conception of new courses and further training offers or the acquisition and implementation of research projects. An important building block in this context is the development of competencies through the acquisition of new professors who contribute their expertise in teaching and research. Rector Professor Dr. Gerhard Schneider explains: “The efficient handling of large amounts of data and their intelligent use holds enormous potential for business, science and society. In future, we want to bundle existing and new activities on this topic in one center under one roof. Relevant regional companies have already indicated their urgent needs and have promised further support. My special thanks go to the Carl Zeiss Foundation, which makes a significant contribution to establishing the center.”

Putting Machine Learning Into Practice

Aalen University of Applied Sciences is known for its competencies in industrial application domains such as mechanical engineering, production, test methods or materials science. Using this knowledge now for questions that will be dealt with at the Center for Machine Learning in the future Ricardo Büttner, who will coordinate the new center, is a special challenge, but also an opportunity. Typical questions are, for example, the prediction of the quality of components in production, the early detection of the need for maintenance of machines or the reliable detection of objects in road traffic by the autonomous Drive. “What is fascinating about machine learning is that once established methods can be quickly adapted to different areas of application such as production, mobility, energy or medicine,” said Büttner.

For more information: www.hs-aalen.de