Research interest

I am interested in uncovering the structural and functional patterns of the human brain development using classical and AI algorithms. My research lies at the intersection of medical imaging (mainly magnetic resonance imaging - MRI), machine learning, and neuroscience – with a focus on developing brains.

Current position

I am a CIBM postdoctoral researcher - working in Campus Biotech in Geneva with MIP:Lab (EPFL & UNIGE – Prof. Dimitri Van De Ville).

Current research

My current line of work focuses on functional MRI analysis mainly with deep learning and/or applied to the analysis of dynamic functional network fluctuations at early age of development.

Past research

After an interlude working on nanoscale structural connectomics before the PhD, my work has zoomed out to the millimeter scale and focused on deep learning applications on biomedical data - mainly on brain MRI. Particularly on diffusion MRI resolution enhancement (1) and white-matter fibers estimation frameworks (2,3,4,5), including in domain shift settings (6,7). I have as well worked on fetal tissue segmentation of structural MRI (8,9,10), also using synthetic data (11,12), and tangentially on eye structures and tumor segmentations (13,14), and on multiple sclerosis detection (15). My most recent past work explored the development of thalamic functional connectivity in neonates using the largest infant cohort to date (16).

Curriculum

I have received a bachelor’s and master’s degree in Communication Systems from EPFL (Switzerland) in 2015, and then pursued a master’s degree in Cognitive Science from Osnabrück University (Germany). In 2017, I worked in the Connectomics department of the Max Planck Institute for Brain Research in Frankfurt. Under the supervision of Prof. Moritz Helmstaedter, I focused on the segmentation and reconstruction of multibeam scanning electron microscopy (mSEM) data using deep neural networks (main results compiled in master thesis). Supported by the Swiss National Science Foundation (SNSF), in 2023 I obtained my PhD thesis in the Life Science program at the University of Lausanne (UNIL) in the Medical Image Analysis Laboratory under the supervision of Prof. Meritxell Bach Cuadra and received the best thesis award in the Faculty of Biology and Medicine (Prix de Faculté). During my PhD, I worked on super-resolution reconstruction of fetal and newborn brains from diffusion magnetic resonance imaging (dMRI) data. In 2022, I was awarded an SNSF Mobility Grant to work as a visiting scholar on fetal and newborn projects at Boston Children’s Hospital & Harvard Medical School with Prof. Ali Gholipour and Prof. Davood Karimi at the Computational Radiology Laboratory. In 2023, I joined the CIBM SP CHUV-UNIL Trustworthy Medical Image Analysis section as a senior SNSF researcher working on the project aiming to tackle domain shifts in early developing brains and between low (0.55T) and higher (1.5T & 3T) field strengths. Since March 2025, I joined the CIBM SP EPFL-UNIGE Connectomic Imaging section.

Distinctions

• Young Investigator Award at the Fetal Infant Toddler Neuroimaging Group conference (2026)
• Best PhD Thesis Award, Faculty of Biology & Medicine, UNIL (2023)
• SNSF PhD Mobility Grant to Harvard Medical School (2022)
• Best educational brain-inspired solution, Donders Institute Hackathon (2016)

Some personal interests

I have a strong interest in discussions around consciousness, meditation (three past 10-days mindfulness Vipassana retreats), psychology, and the « mind » topics in general. Football is a long-standing passion of mine, which I have played for many years (and continue to play) in amateur teams wherever I have lived (Morocco, Switzerland, Germany, and the USA). I also enjoy traveling and experiencing nature in its more raw and impressive forms.