CV
Education
- M.S. in Image & Data, University of Strasbourg, 2020
- Biomedical Engineering Degree, Télecom Physique Strasbourg, 2020
- Ph.D on Uncertainty Quantification for Deep Learning based medical image segmentation, Grenoble Alpes University, May 2024
Work experience
- Since September 2024: Machine Learning Scientific Officer, Pixyl
- Duties include:
- Research and development of medical image analysis software using Deep Learning
- May 2021-May 2024: PhD Student, Pixyl & Grenoble Institut des Neurosciences
- Duties included:
- Development of DL tools for uncertainty quantification in medical image processing
- Medical image synthesis using generative models
- Integration of the tools in a commercialized software
- October 2020-May 2021: Research Enginner, Pixyl
- Duties included:
- Development of DL models for classification/segmentation of 3D MRI
- Calibration of neural networks probability estimates
- Development of Data Augmentation tools
- Mars-August 2020: Graduation Engineering project, Pixyl
- Duties included:
- Deep Learning approaches for unsupervised anomaly detection in 3D medical images
- May-August 2019: Research Internship, Amsterdam AMC, Deparment of Biomedical Engineering & Physics
- Duties included:
- Development of a Generative Adversarial Network (GAN) for CT to CTA translation
- Application to brain vessel segmentation
- June-July 2018: Engineering Internship, Amiens-Picardie University Hospital, Nuclear Medicine Department
- Duties included:
- Implementation of a User-Interface for PET image reconstruction
Skills
- Deep Learning / Machine Learning
- Python, PyTorch, Pytorch Lightning, TorchIO, sklearn, Deep Graph Library, MONAI
- Medical Image processing
Publications
