Luc Vedrenne
I'm a deep learning researcher
Ph.D working on biomedical imaging processing through deep learning. Currenctly working on 3D point clouds registration.
Hi, my name is
About
I just finished my Ph.D, in the IMAGeS team of the ICube lab in Strasbourg, France. I’m now a postdoctoral researcher in the CAMMA team of the same lab, at the IHU, working on automated understanding of surgical procedures through deep learning.
Prior to that, I graduated from the IMT Atlantique engineer school, with a strong emphasis in computer sciences and applied mathematics.
Here are a few fields I've been working on recently:- Optimal transport
- Differential geometry
- Point cloud processing
- Registration algorithm
Experience
Ph.D
-
ICube
Multi-view registration of highly degraded point clouds using deep learning.
- Robust generative registration algorithm (POLAR), leveraging a pretrained VAE latent space to align highly degraded multi-view point clouds: pypolar.github.io/polar.
First-author paper in IEEE Transactions on Image Processing. - Plug-and-play global optimization framework (GRIP) that transforms any local registration method into a global one for non-convex problems: github.com/pcrresearch/GRIP.
- First pure PyTorch implementation of the JRMPC algorithm, 50x runtime improvement: github.com/pcrresearch/JRMPC-PyTorch-Numpy.
- Developed a weakly supervised deep learning pipeline (positive-unlabeled learning) for particle detection in fluorescence microscopy. Reached fully supervised performances with 500x fewer annotations.
- Collaborated with Prof. Paul Guichard & Dr. Virginie Hamel, University of Geneva.
- Contributed to open-source software for biologists: spfluo-app
Sep 2019 - Jan 2020
- Lead PyTorch Developer – designed and implemented deep learning pipelines for cancer detection on CT scans.
- Collaborated with Gustave Roussy Hospital, the largest cancer center in Europe.
Research
2025
Multiview Point Cloud Registration via Optimization in an Autoencoder Latent Space
IEEE Transactions on Image Processing
2024
Optimizing failure mode analysis of dental restorative materials: balancing efficiency and accuracy
International Symposium on Biomedical Imaging (ISBI)
2024
Particle detection based on few shot learning in 3D fluorescence microscopy
International Symposium on Biomedical Imaging (ISBI)
2023
Fast and interpretable unsupervised domain adaptation for FIB-SEM cell segmentation
International Symposium on Biomedical Imaging (ISBI)
Get in Touch
My inbox is always open. Whether you have a question or just want to say hi, I’ll try my best to get back to you!