Master thesis awards 2025
The Mind&Care platform and the MedReSyst community are proud to announce the winners of the 2025 Master Thesis Awards, celebrating outstanding multidisciplinary research at the intersection of healthcare and engineering.
This competition highlights the creativity, rigor, and innovation of young researchers whose work contributes to advancing healthcare systems through engineering approaches.
🥇 1st Place — MRI biomarkers of success of cochlear implant therapy in patients with acquired deafness
Author: Justine Commerman
Affiliation: UCLouvain
Prize: 500 €
This thesis investigates how brain white matter integrity influences auditory recovery after cochlear implantation. Using diffusion MRI from 65 patients, the study analyzed microstructural metrics within key language and audiovisual tracts. Significant correlations were found between pre-operative diffusion measures and early post-implantation auditory scores. These findings suggest that diffusion MRI may help predict cochlear implant outcomes in patients with acquired hearing loss and support more personalized clinical decision-making.
🥈 2nd Place — Preserving Cultural Heritage with AI: Addressing Data Challenges for Museums and Memory Support
Auhtor: Victor Rijks
Affiliation: UCLouvain
Prize: 250 €
This thesis develops an AI-powered search engine to enhance access to and promotion of digital art collections at the Royal Museums of Fine Arts of Belgium, with a focus on activities for Alzheimer’s patients. The resulting “art-models” significantly improve multimodal retrieval and cross-lingual performance. A prototype search engine integrates advanced querying, relevance feedback, and creative management tools. The research demonstrates how AI can support curators, enrich cultural engagement, and aid therapeutic initiatives such as Reminiscence Therapy.
🥉 3rd Place — Advancing Equity in Medical AI: Ensuring Fairness in Pose Estimation Models for Diverse Populations
Author: Manuia Sylvestre-Baron
Affiliation: Multitel
Prize: 250 €
This thesis explores how artificial intelligence can enhance motion analysis in healthcare by improving fairness in human pose estimation models. It addresses bias in datasets that affect model performance across diverse populations. Using diffusion-based generative models for targeted data augmentation, the study enriched underrepresented groups by attributes such as age, gender, and body mass. Results showed improved accuracy and reduced variability across subpopulations, confirming that augmentation promotes fairer and more robust models. The work lays a foundation for more equitable AI applications in medical motion analysis and patient care.
About the Awards
The Master Thesis Awards recognize excellence in multidisciplinary research that bridges healthcare and engineering.
Eligible theses:
- The submitter must belong to the MedReSyst community (UCLouvain, ULB, ULiège, UMons, or UNamur).
- Must have been successfully defended in 2025.
Submissions were evaluated by the MedReSyst committee, who selected the top three theses for their scientific quality, innovation, and potential societal impact.
Congratulations!
We warmly congratulate all participants and their supervisors for their contributions to advancing healthcare research.
