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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. Application for the upcoming winter term starts at September 9th via StudOn!

 

Anne joined the MaD lab in August as an assistant professor. She has a D.Eng. in mechanical engineering from Cleveland State University, and an MSc in mechanical engineering and a BSc in aerospace engineering, both from TU Delft. After starting out in aerospace engineering, she quickly shifted focus...

Traditionally, the University of Erlangen-Nuremberg 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 ...

As Matthias has always been interested in math and physics, he studied both subjects to become a high school teacher. After graduating he continued his studies and enrolled in the Master of Physics program. He worked at the Chair of Applied Physics in Erlangen for three years and focused on building...

Congratulations to Juliana Klein for winning the best poster award at ORTHOKongress in Weiden with her poster on developing algorithms for computing knee stability parameters using a sensor equipped knee sleeve. Also credits to Markus Zrenner for supporting Juliana. Well Done Guys!

Matthias and Philipp had the pleasure to get invited to the VDI Event „Machine Learning@Operations“ to promote two of our projects for industry partners. First of all our joint course ML4Industry (in cooperation with REP and FAPS) offers users in production and quality engineering the possibility to...

Contact

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: irene.steinheimer@fau.de

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