CV
General Information
Full Name | Reuben Dorent |
r[surname]@bwh.harvard.edu | |
Languages | English, French |
Summary | Researcher in Computer Vision for Medical Image Analysis |
Education
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2022 Doctor of Philosophy in Computer Science (Ph.D.)
King's College London - Thesis title: Collaborative learning of joint medical image segmentation tasks from heterogeneous and weakly-annotated data.
- Supervisors: Prof. T. Vercauteren, Prof. S. Ourselin
- Merit: Selected for the King’s Outstanding Thesis Prize 2023
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2018 Master of Science in Mathematics, Vision, Learning (MVA),
Ecole Normale Supérieure (ENS) Paris-Saclay, Cachan, France - Major in: Probabilistic Graphical Models, Kernel Methods, Discrete Inference and Learning
- Thesis title: Learning Tumor And Tissue Segmentation From Disjoint Datasets
- Supervisors: Prof. T. Vercauteren, Prof. N. Paragios
- Merit: Highest Honors
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2018 Diplôme d'Ingénieur in Applied Mathematics
École Centrale Paris, Gif-sur-Yvette, France - Major in: Theory of Probabilities, Modern Applied Statistics, Optimization, Reinforcement Learning
- Supervisor: Prof. N. Paragios
Experience
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2022 - present Postdoctoral Research Fellow
Harvard Medical School, Boston, United States - Registration of pre/intra/post operative MR and ultra-sound images for image-guided brain surgery.
- Supervisor: Prof. S. Wells, Prof. T. Kapur, Prof. A. Golby
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2022 Research Scientist Intern
Hypervision Surgical, London, United Kingdom - Developed a deep learning-based image demosaicking algorithm for snapshot hyperspectral images.
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2018-2022 PhD Student
King’s College London, London, United Kingdom - Collaborative learning of joint medical image segmentation tasks from heterogeneous and weakly-annotated data.
- Supervisor: Prof. T. Vercauteren
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2018 Research Intern
WEISS, University College London, London, United Kingdom - Developed a new approach to perform joint brain tissue and lesion segmentation. Long Oral presentation at MIDL 2019.
- Supervisor: Prof. T. Vercauteren
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2017-2018 MSc Student
École Normale Supérieure Paris-Saclay, Cachan, France - Mathematics, Computer Vision and Machine Learning. Highest Honors.
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2017-2018 MSc Student
École Centrale Paris, Gif-sur-Yvette, France - Applied Mathematics: Probabilities, Statistics, Optimization, Reinforcement Learning.
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2017 Software Engineering Intern,
FrenchFounders, New York, United Statates - Developed and implemented matching algorithms for a networking platform with 2,000 premium business profiles (C-Level, entrepreneurs, VCs). Combined various sources of information (platform logs, text profile descriptions, event attendances).
Prizes and studentships
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2023 - Selected for the King’s Outstanding Thesis Prize
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2021 - Travel Student Award MICCAI 2021
- Honorable Mention Reviewer Award MICCAI 2021
- Best Poster Presentation Award BMEIS School PGR Symposium
Organization of international conferences
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2023 - CrossMoDA Challenge 2023 - MICCAI, Vancouver (October, 8 2023). Lead organizer.
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2023 - Information Processing in Medical Imaging (IPMI) – Bariloche (June, 18-23 2023). Session chair.
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2022 - Boston Medical Imaging Workshop 2022 – Boston (October, 21 2022). Session chair.
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2022 - CrossMoDA Challenge 2022 - MICCAI, Singapore (September, 17 2022). Lead organizer.
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2021 - CrossMoDA Challenge 2021 - MICCAI, online (September, 27 2021). Lead organizer.
Selected Presentations
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2023 - Massachusetts Institute of Technology, MIT CSAIL, Cambridge, United States
- MICCAI 2023, Vancouver, Canada (Poster)
- Inria Paris-Saclay, MIND team, France
- University Rey Juan Carlos, LAIMBIO lab, Madrid, Spain
- Congress of Neurological Surgeons, Washington, United States (Oral presentation)
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2021 - MICCAI 2021, online (Poster)
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2020 - MICCAI 2021, online (Poster)
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2019 - MICCAI 2019, Shenzhen, China (Poster)
- MIDL 2019, London, United Kingdom, (Long Oral presentation)
Editorial positions and peer review
- Editor: Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries, Lecture Notes in Computer Science
- Peer-reviewed Journal: Medical Image Analysis, IEEE Transactions on Medical Imaging, International Journal of Computer Assisted Radiology and Surgery, Machine Learning for Biomedical Imaging
- Peer-reviewed Conference: MICCAI, MIDL