Traditionally, the Friedrich-Alexander University of Erlangen-Nürnberg (FAU) is an exemplary location for Artificial Intelligence (AI), pattern recognition and machine learning. Already in 1975, Prof. Heinrich Niemann established the first chair dealing with AI. His work on pattern recognition yielded fundamental research in the areas of computer vision, speech comprehension and medical imaging. After FAU has raised numerous additional research topics around AI, the Machine Learning and Data Analytics lab was just founded in 2017, supported by a Heisenberg Professorship by the DFG. Further, John McCarthy, the inventor of the AI, holds an honorary doctorate from the FAU. Based on its extant AI research, FAU has compiled five clusters that are presented in the FAU AI Map. Thereby, this page provides an overview of AI research at FAU, presenting its professors, AI research fields and affiliated industry partners.


Graphic: M. Zimmerhackel


Currently, more than 60 chairs and professorships are working on crucial AI topics. The FAU researchers focus on, for instance, foundations of mathematics, algorithmics, their computation for embedded systems or data security. The applications are not only in the medical context, manufacturing or digital humanities, but address also overarching issues such as ethical aspects of AI. The latter is represented by Prof. Dabrock, Chairman of the German Ethics Council and professor at FAU. Following the motto “Knowledge in Motion”, FAU disseminates and further pushes its research in numerous collaborations with excellent research institutes and renowned industry partners – focusing on AI research fundamentals and the four clusters: Comprehensive AI, AI in Medicine, AI in Manufacturing, and Embedded AI. Discover the five FAU AI clusters by clicking on the following buttons.


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Image: Colourbox

Comprehensive AI

MRI Brain Scan
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AI in Medicine

Image: FAU/B. Mijat

AI in Manufacturing

Finger pressing a push button to start a self-driving car.
Image: Colourbox

Embedded AI

Image: FAU/G. Pöhlein

AI Research Fundamentals