50 years of pattern recognition: FAU celebrates pioneering work in AI!

50 years of pattern recognition: FAU celebrates pioneering work in AI!

On October 14, 2025, the Chair of Pattern Recognition at Friedrich Alexander University (FAU) celebrated its 50th anniversary. This marks an important milestone for an institution that is considered a pioneer in artificial intelligence (AI) in Germany. FAU was the first university in the country to establish such a chair, laying the foundation for numerous developments in the field of pattern recognition and machine learning.

The chair, which was founded by Heinrich Niemann in 1975, played a crucial role in research into the automatic classification of image content and machine speech recognition. While the technology landscape has changed greatly since those early days, the importance of pattern recognition in AI remains undiminished. “The development of AI was not predictable back then,” say the researchers, “as the available data volumes and memory sizes were small.” Today, thanks to advances in computing resources and algorithms, AI models can automatically learn from large amounts of data.

The path to modern artificial intelligence

Today, common methods are based on statistical methods that make it possible to recognize patterns in data. Algorithms, especially neural networks, have made significant progress in recent years. The first ideas about neural networks were developed in the early years of the department, but they only experienced a breakthrough with the introduction of fast graphics processors and wider Internet penetration.

Over 20 research groups at FAU are active in current research. These focus on various aspects of AI, including assistive intelligent robotics, mathematical foundations of machine learning and applications in the digital humanities. In 2017, the Machine Learning and Data Analytics Lab (MaD Lab) was launched, and in 2020 the departments for Artificial Intelligence in Biomedical Engineering (AIBE), Data Science (DDS) and Digital Humanities and Social Studies (DHSS) were founded with a clear focus on interdisciplinary approaches.

Challenges and social implications

Despite the impressive advances in AI, there are still challenges. There are problems that AI cannot solve, such as understanding unknown languages ​​or recognizing vocalizations without context. Nevertheless, researchers see both the opportunities and potential threats associated with the development of AI. Some job profiles could be jeopardized, while at the same time new, creative freedom is created.

A central component of FAU is training, which, in addition to research, places great emphasis on the ethical implications of AI. The faculty members, including Prof. Ivan Dabrock and Prof. Vincent Müller, address the social impacts of these technologies. The topic of AI ethics is organized into five main research clusters: AI Foundations, Comprehensive AI, Embedded AI, AI4health and AI Ethics & Societal Impact. The last two clusters are particularly relevant as Erlangen is considered a health hub within Bavaria's high-tech agenda, and AI is increasingly being applied in areas such as health, manufacturing and digital humanities.

The challenges FAU faces are numerous, but ongoing research and development is making a crucial contribution to shaping the future of artificial intelligence. The Chair of Pattern Recognition remains a linchpin in this exciting and rapidly evolving discipline that will be ubiquitous in the years to come.

For further information, FAU offers, among other things, comprehensive insights into the area of ​​artificial intelligence on its website fau.de as well as further details about their research activities ai.fau.digital and background information on artificial intelligence wirtschaftsforum.de.