Welcome to the MaD Lab!

The researchers in the Machine Learning and Data Analytics (MaD) lab conduct theoretical and applied research for wearable computing systems and machine learning algorithms for engineering applications at the intersection of sports and health care. Our motivation is generating a positive impact on human wellbeing, be it through increasing performance, maintaining health, improving rehabilitation, or monitoring disease.

Home of the Innovation Lab

The MaD Lab is the home of the Innovation Lab for Wearable and Ubiquitous Computing, where students develop innovative prototypes with industry partners.

Register now via Studon!


We were happy that the Bavarian Minister for Digitalization Judith Gerlach visited FAU Erlangen-Nürnberg and its surrounding #Digital#Health #Ecosystem with the German #DigitalHealthHub on March 27th. Zollhof - Tech Incubator FAU Germany Medical Valley EMN

On February 26, Markus and Philipp were invited to join the meetup of all Bavarian Innovation Labs in Augsburg. This event was hosted by the University of Augsburg and the University of Applied Sciences Augsburg under the umbrella of Zentrum Digitalisierung.Bayern (ZD.B). Every semester, these meeti...

On March, 07th Markus and Philipp participated in a certificated Design Thinking workshop at “JOSEPHS – The open innovation lab” in Nuremberg. Together with other colleagues of the Digital Tech Academy and the Zollhof Tech Incubator, they got valuable insights in Design Thinking and Service Desig...

Felix and Martin spent a few days of work shadowing with Jeffrey Hausdorff in Tel Aviv via the Erasmus-Staff-Training-Week program [1]. Prof. Hausdorff is a professor at Tel-Aviv University and the director of the Center for the Study of Movement Cognition and Mobility (CMCM) at the Tel-Aviv Sourask...

Nicolae studied Physics Engineering at the Ankara University. Afterwards, he continued with masters at FAU in advanced optical technologies, where he majored in computational optics and optics in medicine. His master thesis was focused on the application of deep learning techniques for the classific...


Irene Steinheimer

  • Organization: Department of Computer Science
  • Address:
    Carl-Thiersch-Straße 2b
    Room 01.017
    91052 Erlangen
  • Phone number: +49 9131 85 28990
  • Fax number: +49 9131 85 28980
  • Email: