Delphine Ribes
Delphine Ribes Lemay, Head of Creative Coding at EPFL+ECAL Lab, is an electrical engineer and originally specialized in medical image processing.
She leads the software and Artificial Intelligence approach on EPFL+ECAL Lab’s research projects. She is also responsible for the medical and healthcare research at the lab.
Besides her research activities, she is a lecturer at EPFL+ECAL Lab where she teaches machine learning and creative coding on the MAS. At EPFL, she gives courses where she shares her experiences in working in pluridisciplinary and start-up environments.
Related projects
Scientific publications
A comparative study of deep learning for cortical lesion MRI segmentation with explainability analysis in multiple sclerosis
Nataliia Molchanova, Alessandro Cagol, Mario Ocampo–Pineda, Po–Jui Lu, Matthias Weigel, Xinjie Chen, Erin S. Beck, Charidimos Tsagkas, Daniel S. Reich, Colin Vanden Bulcke, Anna Stölting, Serena Borrelli, Pietro Maggi, Sebastian Baez Lugo, Delphine Ribes, Adrien Depeursinge, Cristina Granziera, Henning Müller, Pedro M. Gordaliza, Meritxell Bach Cuadra. (2026). A comparative study of deep learning for cortical lesion MRI segmentation with explainability analysis in multiple sclerosis. NeuroImage: Clinical, 104007.
NeuroImage: Clinical
Advances on Real Time M/EEG Neural Feature Extraction.
Payam S. Shabestari, Delphine Ribes, Lara Défayes, Danpeng Cai, Emily Groves, Harry H. Behjat, Dimitri Van de Ville, Tobias Kleinjung, Adrian Naas, Nicolas Henchoz, Andreas Sonderegger, and Patrick Neff. 2025. Advances on Real Time M/EEG Neural Feature Extraction. In 2025 IEEE 38th International Symposium on Computer-Based Medical Systems (CBMS), June 2025. 337–338.
International Symposium on Computer-Based Medical Systems (CBMS)