Mauricio is a Marie Curie fellow working on the “Dementia modeling Project” (DEMO). His research project involves the development of Deep machine learning models for the analysis and semantic segmentation of multimodal imaging data, with a particular focus on advanced Domain Adaptation methodologies in order to increase the robustness to missing modalities, dealing with differences in image resolution, with the ultimate aim of extracting stable, robust and clinically relevant imaging-derived biomarkers for different sub-types of dementia, such as Alzheimer’s disease and vascular dementia. He received his B.Sc degree in Electronic Engineering and an M.Sc. degree in Engineering from Universidad Nacional de Colombia. During his master’s, he also joined the Signal Processing and Pattern Recognition Group where he had the opportunity to work on several research projects in the field of neuroscience. His motivation to research this topic relies on his enthusiasm for the improvement of people’s life quality through the development of computational applications.
ProjectsNeurology - Dementia
Orbes-Arteaga, M., Varsavsky, T., Sudre, C.H., Eaton-Rosen, Z., Haddow, L.J., Sørensen, L., Nielsen, M., Pai, A., Ourselin, S., Modat, M. and Nachev, P., 2019. In Domain Adaptation and Representation Transfer and Medical Image Learning with Less Labels and Imperfect Data (pp. 54-62). Springer, Cham.