Supervisor: Torsten Möller, Christoph Thiem, Judith Staudner
Within the AIROW (artificial intelligence in rowing) project (https://airow.univie.ac.at/) we are collaborating with sports scientists, the Austrian Rowing Federation, and other Data Scientists to collect, curate, and analyse data from top rowers on the training process, recovery, wellbeing and health.
Some of the main questions of the project is to better understand optimal training regimes as well as the impact of training, well-being, and other factors on the athlete's performance in order to optimize training load management.
Within this project, we have a number of student projects that aim at:
- Power Meter Data Analysis
This project explores the analysis, clustering, and visualization of cycling power meter data.
The aim is to identify recurring patterns and gain new insights for training and performance analysis.
- Detection of Faulty and Incorrect Data in AIROW
This project focuses on identifying faulty, implausible, or suspicious data in AIROW. Examples include repeated self-report entries, incorrect manual inputs, and problematic physiological signals such as HR or power dropouts.
In order to participate, you need to have passed (and enjoyed) the FDA course (Foundations of Data Analysis). The supervision will be done by various members of the project team. For more information, please contact Torsten M.
Prerequisites: FDA
Contact: Torsten Möller, Christoph Thiem, Judith Staudner