Hamza Kebiri

Hamza Kebiri is a Researcher at the Center for Biomedical Imaging (CIBM), currently affiliated with the EPFL-UNIGE Network Analysis and Functional MR Imaging Section since March 2025, following his 2023 appointment to the CHUV-UNIL Computational Neuroanatomy & Fetal Imaging Section. His work bridges biomedical engineering and clinical neuroimaging through advanced computational methods.

His academic foundation includes:

• Bachelor’s and Master’s in Communication Systems from École Polytechnique Fédérale de Lausanne (EPFL), Switzerland
• Master’s in Cognitive Science (Neuroinformatics & Neuroscience) from Osnabrück University, Germany

Dr. Kebiri’s research centers on neuroscience-driven machine learning applications for medical imaging, specializing in super-resolution reconstruction of fetal/newborn brains from diffusion MRI. He addresses critical challenges in domain adaptation across developmental stages (fetal vs. neonatal) and magnetic field strengths (0.55T–3T), leveraging deep neural networks for segmentation and quantitative mapping. His expertise spans multibeam electron microscopy analysis and low-field MRI optimization.

His scientific recognition includes the FNS Mobility Grant (2022), enabling collaborative research at Boston Children’s Hospital & Harvard Medical School.

Funded by Swiss National Science Foundation projects (182602 and current senior researcher role), he develops cross-population imaging frameworks while maintaining active partnerships with Harvard’s IMAGINE group. No formal student advisement is documented.

His research trajectory spans the Max Planck Institute’s Connectomics department, Boston Children’s Hospital, and CIBM’s TESSERACT Data Science initiative, driving innovations in fetal neuroimaging infrastructure and 7T MRI collaboration networks.