Prof. Dr. Anne Koelewijn

Chair of Machine Learning and Data Analytics Lab

It is my goal to improve movement for people, e.g. those with a disability or athlete. To do so, I aim to better understand human motion, and design better devices, such as prostheses, exoskeletons, and running shoes, as well as prevent injuries, such as knee osteoarthritis. I focus on wearable technologies and the combination of physics-based models with machine learning methods.

Research projects

Personalized musculoskeletal models and gait simulations: using imaging techniques such as diffusion tensor imaging (DTI), as well as using machine learning methods, we aim to personalize musculoskeletal models and gait simulations, such that we can per

  • Bridging the gap in ACL injury prevention with FAME: Field-based Athlete Motion Evaluation and simulation

    (Third Party Funds Single)

    Term: since 15. January 2024
    Funding source: Deutsche Forschungsgemeinschaft (DFG)

2025

2024

2023

2022

2021

2020

Related Research Fields

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