1 avenue du Dr. Albert Schweitzer, 33400 Talence, France
michael.clement@enseirb-matmeca.fr
I am associate professor of computer science (maître de conférences) at Bordeaux INP, in the ENSEIRB-MATMECA engineering school, and researcher at the LaBRI laboratory, in the Image and Sound department. My main research interests are computer vision, image analysis, deep learning and artificial intelligence.
I obtained my PhD in computer science from Université Paris Descartes, where I was advised by Laurent Wendling and Camille Kurtz. My work was about modeling and learning spatial relations between objects for image understanding, with applications in document analysis, remote sensing and medical imaging. After my PhD, I was a postdoctoral researcher at the Centre for Vision Research of York University, where I worked with James Elder on shape data analysis for 2D and 3D reconstruction problems.
My research activities take place at the LaBRI, in the Image and Sound department. Since 2022, I am co-head (with Jean-Luc Rouas) of the Traitement et Analyse de Données (TAD) research team. I am also a member of the In2Brain research group.
| Name | Date | Subject |
|---|---|---|
| Corentin Seutin | 2025–… | Image segmentation guided by large language models |
| Julien Walther | 2024–… | Deep learning models from structural image representations |
| Logan Servant | 2023–… | Integrating spatial relations in deep representation learning |
| Manuel Ricardo Guevara Garban | 2022–… | Hybrid physics-AI models for multiscale simulation of architectured materials |
| Hernán Carrillo | 2020–24 | Guiding neural networks for image colorization through user interactions |
| Huy-Dung Nguyen | 2020–23 | Deep learning for the detection of neurological diseases |
| Name | Date | Subject |
|---|---|---|
| Mohamed Amine Ettaki | 2025 | Image segmentation guided by large language models |
| Roland Kia | 2025 | Automatic radar profile recognition |
| Corentin Seutin | 2025 | Image segmentation guided by large language models |
| Corentin Seutin | 2024 | Evaluation metrics for MRI brain segmentation |
| Fabien Pelletier | 2023 | Deep learning for multisite MRI harmonization |
| Nolan Bizon | 2023 | Segmentation of 3D archeological samples |
| Adrien Aguila--Multner | 2023 | Deep learning from irregular image representations |
| Lisa Weisbecker | 2023 | Deep learning from irregular image representations |
| Pierre Pavia | 2022 | Deep learning from irregular image representations |
| Maëlle Andricque | 2021 | Image colorization with deep learning |
| Baptiste Bénard | 2021 | Image colorization with deep learning |
| Sohaib Errabii | 2021 | Learning spatial relationships with deep neural networks |
| Zaid Zerrad | 2021 | Auto-supervised learning and transformers for computer vision |
| Eduardo Daniel Bravo Solis | 2020 | Deep learning for semantic segmentation of LiDAR point clouds |
| Shanshan Zhao | 2020 | Deep learning from structural image representations |
| Arthur Longuefosse | 2020 | Irregular dual representations for image processing |
| Otavio Flores Jacobi | 2020 | Graph neural networks for image generation |
| Merlin Boyer | 2019 | Matching algorithms for irregular structures |
| Name | Date | Type |
|---|---|---|
| AIKNEE | 2026–29 | ANR PRCE (WP manager) |
| FUNERIA | 2025–27 | UB Recherche Interdisciplinaire et Exploratoire (PI) |
| RADAR | 2025 | GIS Albatros (PI) |
| SegLLM | 2025 | UB Département SIN (PI) |
| HoliBrain | 2023–27 | ANR PRC (member) |
| IA-SeReOS | 2023–24 | CNRS MITI Interdisciplinaire (member) |
| NAS brain | 2023 | ENLIGHT (member) |
| VITAS | 2021 | UB Département SIN (PI) |
| DeepVolBrain | 2019–23 | ANR JCJC (member) |
| PostProdLEAP | 2019–23 | ANR PRCE (member) |
| APRES | 2019–20 | GdR IASIS (PI) |
I teach computer science at ENSEIRB-MATMECA, a public engineering school located in Bordeaux. Since 2022, I am head of the last-year specialization in AI (M2) at ENSEIRB-MATMECA. Before that, I was head of first year for the R&I work-study programme.
| Name | Level |
|---|---|
| Machine learning | 3A IA (M2) |
| Deep learning | 3A IA (M2) |
| Computer vision | 3A IA (M2) |
| Artificial intelligence projects | 3A IA, 3A TSI (M2) |
| Introduction to artificial intelligence | 3A R&I (M2) |
| Introduction to machine and deep learning | 2A info (M1) |
| Artificial intelligence | 2A info (M1) |
| Algorithms and programming projects | 1A info (L3) |
| C programming | 1A R&I (L3) |
At ENSEIRB-MATMECA
| Name | Level |
|---|---|
| Image processing for robotics | 3A robot (M2) |
| Object-oriented programming | 2A info (M1) |
| Software engineering projects | 2A info (M1) |
| UNIX, GNU/Linux environment | 1A info (L3) |
At Université Paris Descartes (2014–17)
| Name | Level |
|---|---|
| Pattern recognition | M1 info |
| Image processing | L3 info |
| Algorithms and data structures | L2 info |
| Introduction to programming | L1 maths-info |