About me

  • MICCAI 2017: Our two papers on Graph CNNs for brain analysis have been accepted at MICCAI 2017. Code available on Github and preprints available on arxiv: here and here.
  • MICCAI 2017: I am co-organising the workshop on Graphs in Biomedical Image Analysis in the afternoon of Thursday 14/09/2017. Please consider to submit your work until 12/06/2017!
  • NeuroImage: Our survey of brain parcellation methods is now available. More details at https://biomedia.doc.ic.ac.uk/brain-parcellation-survey/ .
  • I am a Research Associate at the Biomedical Image Analysis Group at Imperial College London working with Prof. Daniel Ruerckert . After graduating from the Ecole Centrale Paris, one of France’s top engineer schools, I did my PhD in the Center for Visual Computing at Ecole Centrale Paris under the supervision of Prof. Nikos Paragios. There, I worked on brain tumour analysis, with a strong focus on segmentation, clustering methods and atlas construction. My PhD was also partly funded by Intrasense, a french start up developing medical imaging softwares and we worked closely with Prof. Hugues Duffau, a world renown neurosurgeon specialised on diffuse low-grade gliomas.

    Over the course of my PhD, I visited the Surgical Planning Laboratory at Harvard Medical School for three months where I was supervised by Prof. William Wells III. I extended my work on tumour segmentation and registration for pre-operative and intra-operative brain registration for tumour resection.

    After finishing my PhD in 2013, I joined the Biomedical Image Analysis Group to work on the developing human connectome project (dHCP). The dHCP is an ERC synergy grant programme in collaboration between King’s College London, Imperial College London and Oxford University. The aim of the project is to create and study the first 4-dimensional brain connectivity map of early life.

    My research focuses on graph-based methods for brain analysis and disease detection. Under the scope of the dHCP, I have been developing methods for connectivity-driven brain parcellation through spectral clustering and Markov Random Field models. More recently, I have explored the concept of deep learning on graphs for brain analysis.

    I recently co-organised the first dHCP workshop on Big Data Initiatives for Connectomics Research as a satellite event for the 2015 International Conference Brain Informatics and Health (BIH).


    Biomedical Image Analysis Group
    Dept of Computing
    180 Queen’s Gate
    Imperial College London
    London SW7 2AZ, UK