Scholar
Benjamin Billot
Google Scholar ID: NhRVLT8AAAAJ
Researcher, Inria
Citations & Impact
Citations
2,171
H-index
18
i10-index
24
Publications
20
Co-authors
10
list available
Publications
Resume (English only)
Academic Achievements
- Published multiple papers, including a paper in PNAS on SynthSeg+, which presents a robust machine learning segmentation method for large-scale analysis of heterogeneous clinical brain MRI datasets; also published a preprint accepted at WCACV 2024 on domain randomisation for segmentation of star-shape objects.
Research Experience
- Worked as a member of the AI team at Founders Factory, an incubator of start-ups; currently working on various projects including equivariant networks, registration of fetal MRI, and unifying disjoint manual annotation databases to train unified segmentation models at MIT.
Education
- Completed a MSc in neuro-technology at Imperial College London in 2016; pursued a PhD at University College London with Dr. Juan Eugenio Iglesias on developing a domain randomisation strategy for domain-agnostic segmentation of brain MRI (SynthSeg).
Background
- Postdoc at the Medical Vision Group led by Prof. Polina Golland, focusing on improving data representation to increase the robustness of systems for the analysis of clinical imaging data.
Miscellany
- Co-organized the Boston Medical Imaging Workshop and presented work on equivariant networks for registration of fetal brain MRI at MIDL 2023.
