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About Me

Pierre-Antoine Comby
Author
Pierre-Antoine Comby
PhD in AI and Neuroimaging
Google Scholar
Table of Contents

Biography
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I got a PhD on “Physics and Medical Imaging” from Universite Paris-Saclay, after my work at the interface between Deep learning, Inverse Problems and Neuroscience in the MIND and METRIC Team at Inria and Neurospin, at CEA Saclay (France), supervised by Philippe Ciuciu and Alexandre Vignaud.

I am working on innovative functional MRI acquisition and reconstruction methods using deep learning. I foster reproducible science and contribute to open-source software.

My résumé

My thesis manuscript and the recording of my thesis defense

pierre-antoine.comby@(cea|inria|ens-paris-saclay).fr

Interests

  • Deep Learning
  • Inverse Problem
  • Biomedical Imaging
  • Open Source

Education

PhD in Deep Learning and Inverse Problem University Paris Saclay, 2021-2025
MSc Control, Signal and Image Processing University Paris Saclay, 2020-2021
Normalien Élève Ecole Normale Supérieure Paris-Saclay, 2017-2021

IEEE Style
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Pierre-Antoine Comby is currently a Ph.D. student of the University Paris-Saclay, in the MIND Team (CEA/Inria), under the supervision of Dr. Philippe Ciuciu and Dr. Alexandre Vignaud. He received his M.Sc. in Signal Processing from the Ecole Normale Supérieure Paris-Saclay in 2021. His research interests include signal processing, machine learning, and computational neuroscience. He is particularly interested in the development of new methods for functional MRI reconstruction, with a focus on high-resolution imaging and accelerated acquisition.

Pierre-Antoine Comby published in several international conferences, including the IEEE International Symposium on Biomedical Imaging (ISBI), the International Society for Magnetic Resonance in Medicine (ISMRM). He has been a reviewer for the IEEE Transactions on Medical Imaging, the IEEE Transactions on Computational Imaging, as well as for the Magnetic Resonance in Medicine journal.

Awards & Grants
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Best Abstract Award (ISMRM 2024)
2nd Place, Reproducible Research Group
CDSN Grant (2021-2024)
Doctoral Funding from École Normale Supérieur Paris-Saclay for challenging PhD topics.
Normalien Élève (2017-2021)
4 year Funding for Graduate school as a civil servant

Publications
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Reviews
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I have peer reviewed several submissions for the following Journals:

Journal
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Conference Proceedings
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Comby, P.-A., Daval-Frerot, G., Gr, C., Vignaud, A., & Ciuciu, P. (2024). Mri-nufft: An open source python package to make non-cartesian mr imaging easier. Ismrm Annual Meeting, (in Press).
Comby, P.-A., Vignaud, A., & Ciuciu, P. (2024). Snake-fmri: A modular fmri simulator from the space-time domain to k-space data and back. Ismrm Annual Meeting, (in Press).
Z. Amor, Comby, P.-A., Ciuciu, P., & Vignaud, A. (2024, May). Achieving high temporal resolution using a sliding-window approach for sparkling fmri data: a simulation study. Ismrm Annual Meeting.
Amor, Z., Comby, P.-A., Ster, C. L., Vignaud, A., & Ciuciu, P. (2023). Non-cartesian non-fourier fmri imaging for high-resolution retinotopic mapping at 7 tesla. 2023 Ieee 9th International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (Camsap), 201–205. https://doi.org/10.1109/CAMSAP58249.2023.10403497
Comby, P.-A., Amor, Z., Vignaud, A., & Ciuciu, P. (2023, April 18). Denoising of fmri volumes using local low rank methods. Isbi 2023 - international symposium on biomedical imaging. https://hal.science/hal-03895194
Comby, P.-A., Amor, Z., Vignaud, A., & Ciuciu, P. (2023, June). Benchmarking local low rank denoising methods for task-based fmri data analysis. Ismrm 2023 Annual Meeting.
Hopp, T., Zuch, F., Comby, P.-A., & Ruiter, N. V. (2020). Fat ray ultrasound transmission tomography: Preliminary experimental results with simulated data. Medical Imaging 2020: Ultrasonic Imaging and Tomography, 11319, 113190M. https://doi.org/10.1117/12.2548444

Coworkers and Collaborators
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  • Dr. Philippe Ciuciu
  • Dr. Alexandre Vignaud
  • Dr. Emilie Chouzenoux
  • Dr. Matthieu Terris
  • Dr. Chaithya G. R.
  • Dr. Zaineb Amor
  • Marie Dogo (Supervised M.Sc. intern, Summer 2023)
  • Benjamin Lapostolle (Supervised M.Sc. intern Summer 2024)

Numerical IDs
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ORCID: 0000-0001-6998-232X

GPG: 73E0 23DD 46BD EF3C 5697 C344 1B97 78EB B070 A4BF