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 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…

Master’s Thesis Accurate survival prediction is essential for optimizing treatment strategies and clinical decision-making in patients with chronic diseases. Traditional survival models, such as Cox proportional hazards rely on static baseline covariates and do not account for evolving patient conditions. Advances in causal inference and machine learning enable dynamic survival models that adapt to longitudinal…

Research Project Depression is one of the most common mental health disorders, significantly reducing an individual’s quality of life. Psychologists use various methods to detect and assess depression, such as analysing facial expressions, speech patterns, and head movements. In this research, our goal is to study speech patterns and voice. This study is part of…

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News

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…

We are delighted to announce that Dr. Janina Beilner has received her certificate as a professor on 25.03.2025 and is now officially an Honorary Professor at the Machine Learning and Data Analytics Lab. We look forward to continuing our collaboration with her in this new role. Congratulations to Prof. Dr. Janina Beilner on this well-deserved…

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