CIBM | Center for Biomedical Imaging

Hamza Kebiri joined the CIBM SP CHUV-UNIL Computational Neuroanatomy & Fetal Imaging Section in September 2023. 

Hamza Kebiri received a bachelor’s and master’s degree in Communication Systems from the Ecole Polytechnique Fédérale de Lausanne (EPFL) in Switzerland, and a master’s degree in Cognitive Science (Neuroinformatics & Neuroscience) from Osnabrück University, in Germany. In 2017, he joined the Connectomics department of the Max Planck Institute for Brain Research in Frankfurt. Under the direction of Prof. Moritz Helmstaedter, he focused on the segmentation and reconstruction of multibeam scanning electron microscopy (mSEM) data using deep neural networks.

Between 2019 and 2023, he performed a PhD thesis in the Life Science program of Lausanne University under the supervision of Dr. Meritxell Bach Cuadra, supported by the Swiss National Science Foundation (SNSF) project 182602. In his PhD project, he worked on super-resolution reconstruction of fetal and newborn brains from diffusion magnetic resonance imaging (dMRI) data. In 2022, he was awarded an FNS Mobility Grant to work as a visiting scholar on fetal and newborn projects in the IMAGINE group at Boston Children’s Hospital & Harvard Medical School in the USA with Prof. Ali Gholipour and Prof. Davood Karimi, with whom collaboration is still ongoing.

Dr. Kebiri started as a senior FNS researcher in the project aiming to tackle domain shifts in the reconstruction, segmentation, and quantitative mappings between newborn and fetal populations and between high (1.5T & 3T) and low (0.55T) field strengths. Hamza’s broad research interest encompasses neuroscience, brain reconstruction, machine learning, and its applications to medical neuroimaging.

KEYWORDS: low field, MRI, image reconstruction, fetal population, machine learning