About the Machine Learning and Data Analytics 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.

The registration for the Innolab in the summer term 2018 starts on the 5th of March! Students can register via Studon!

Recent News

On Schüler-Infotag more than 400 students from different schools took a look at the research at FAU. Martin and Malte presented projects of the MaD Lab in the fields of movement analysis and virtual reality. In hands-on demos the students learned that wearable sensing is already a part of our everyd...

In gemeinsamer Zusammenarbeit zwischen der FAU und der UKER konnte unter der Federführung der Molekularen Neurologie ein EIT-Health Projekt eingeworben werden, welches die Sensor-basierte Gang- und Sturzanalyse bei Parkinson-Patienten entwickelt. Die Kombination von Bewegungssensoren im Schuh zur ho...

We are pleased to announce that our paper “Promoting Relaxation Using Virtual Reality, Olfactory Interfaces and Wearable EEG” by Judith Amores (MIT Media Lab) and Robert Richer (MaD Lab) won the Best Student Paper Award at the 2018 IEEE International Conference on Body Sensor Networks (BSN) in Las V...

First studying Biophysics and Biomedical Engineering, Arne realized that building software and developing algorithms is a lot more fun. After a master thesis on monitoring human joint angles with wearables sensors, he now joined the team as a doctoral researcher on the MoveIT project, which aims ...


Irene Steinheimer

  • Organization: Department of Computer Science
  • Address:
    Immerwahrstr. 2a
    Room 1.004
    91058 Erlangen
  • Phone number: +49 9131 85 28990
  • Email: