Machine Learning and Data Analytics Lab

As of 1 October 2025, Prof. Eskofier has assumed his main position at Ludwig-Maximilians-Universität München. He remains affiliated with Friedrich-Alexander-Universität Erlangen-Nürnberg and Helmholtz München. The Machine Learning and Data Analytics (MaD) Lab is currently in a transitional phase. However, our research in machine learning and data analytics for sports and healthcare remains active, and teaching activities and thesis supervision continue without interruption. Please check back later for further updates.

Research

Teaching

Teaching

The MaD Lab offers a variety of options for students in various degree programs and degrees.

Student courses
Teaching

Student Theses and Jobs

Research Project We are offering two Master’s projects (10 ECTs) focused on the practical application of 3D human pose estimation.  This project connects hardware setup with software applications by creating a multi-camera data collection system and deploying advanced pose-estimation models to analyze the captured data. The student will be responsible for the end-to-end process of…

Background: It has been shown that the longitudinal bending stiffness of shoes influences running and sprinting performance. To maximize performance, this stiffness should not be set to maximum, but rather to an individual level. While the optimal longitudinal bending stiffness differs between individual athletes, the target can not be linked to a single discrete parameter…

Research Internship / Project Background: The effects of excessive social media use remain a relatively underexplored area. Given how common and frequent smartphone use has become, this topic is currently a relevant research field. Among other things, it raises the question of whether frequent social media use has (negative) effects on human physiology. The aim…

More

News

Background: It has been shown that the longitudinal bending stiffness of shoes influences running and sprinting performance. To maximize performance, this stiffness should not be set to maximum, but rather to an individual level. While the optimal longitudinal bending stiffness differs between individual athletes, the target can not be linked to a single discrete parameter…

We are proud to share our latest study, published in MDPI Audiology Research, in collaboration with WS Audiology! Together, we explored how hearing aid amplification affects gait performance using hearing-aid integrated motion sensors. Our study showed that in low cognitive demand settings, amplification doesn’t significantly change walking, but it highlights the huge potential of earables for…

We are excited to share our latest study, published in JMIR Human Factors, which resulted from a collaboration with the amazing team from ProCarement GmbH. Together, we explored how we can support patients through better knowledge transfer and patient engagement in their digital health app ProHerz. Working with ProCarement allowed us to combine research and…

More

Upcoming Events

    No events scheduled.