Picture of Michaël Clément

Michaël Clément

Associate professor of computer science

Bordeaux INP - ENSEIRB-MATMECA logo LaBRI logo
Research
LaBRI - UMR CNRS 5800
351 cours de la Libération, 33400 Talence, France
Teaching
Bordeaux INP - ENSEIRB-MATMECA
1 avenue du Dr. Albert Schweitzer, 33400 Talence, France

About me

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.

[2018–…]
Associate professor of computer science, Bordeaux INP, Bordeaux, France
Research at the LaBRI, in the Image and Sound department (co-head of the TAD team)
Teaching at the ENSEIRB-MATMECA engineering school (head of the AI track)
[2017–18]
Postdoctoral researcher, Centre for Vision Research, York University, Toronto, Canada
Project: Sparse dictionary learning from shape data
Advisor: James Elder
[2014–17]
PhD in computer science, LIPADE, Université Paris Descartes, Paris, France
Thesis title: Modeling and learning spatial relations for image recognition and understanding
Advisors: Laurent Wendling and Camille Kurtz
Teaching assistant at the UFR Mathématiques et Informatique
[2013–14]
Master's degree in computer science, Université Paris Descartes, Paris, France
Research internship at the LIPADE
Advisors: Laurent Wendling and Camille Kurtz
[2010–13]
Engineer's degree in computer science and applied mathematics, Grenoble INP - Ensimag, Grenoble, France
Software engineer apprentice, STMicroelectronics
[2008–10]
DUT informatique, Université Paris Sud, Orsay, France
Software developer apprentice, IBM Delivery Services

Research

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.

Publications

2026

[j10]
SpIRL: Spatially-aware image representation learning under the supervision of relative position descriptors
Logan Servant, Michaël Clément, Laurent Wendling, Camille Kurtz
Pattern Recognition, 2026

2025

[j9]
Physics-informed graph neural networks to reconstruct local fields considering finite strain hyperelasticity
Manuel Ricardo Guevara Garban, Yves Chemisky, Michaël Clément, Étienne Prulière
International Journal for Numerical Methods in Engineering, 2025
[c15]
Superpixel Anything: A general object-based framework for accurate yet regular superpixels
Julien Walther, Rémi Giraud, Michaël Clément
British Machine Vision Conference (BMVC), 2025
[c14]
Contrastive learning of image representations guided by spatial relations
Logan Servant, Michaël Clément, Laurent Wendling, Camille Kurtz
Winter Conference on Applications of Computer Vision (WACV), 2025
[cn8]
Réseaux de neurones par graphes informés par la physique pour la reconstruction de champs de contraintes mécaniques
Manuel Ricardo Guevara Garban, Yves Chemisky, Michaël Clément, Prulière Étienne
Journées francophones des jeunes chercheurs en vision par ordinateur (ORASIS), 2025
[cn7]
Apprentissage contrastif de représentations d'images guidée par les relations spatiales
Logan Servant, Michaël Clément, Laurent Wendling, Camille Kurtz
Journées francophones des jeunes chercheurs en vision par ordinateur (ORASIS), 2025
[a5]
Fouille virtuelle d’urnes funéraires assistée par IA: une étude de cas
Nicolas Vanderesse, Michaël Clément, Romane Martin, Stéphane Rottier
IA et innovations numériques : usages et enjeux en archéologie, 2025

2024

[j8]
Brain Structure Ages — A new biomarker for multi-disease classification
Huy-Dung Nguyen, Michaël Clément, Boris Mansencal, Pierrick Coupé
Human Brain Mapping, 2024
[c13]
Deep spherical superpixels
Rémi Giraud, Michaël Clément
International Conference on Pattern Recognition (ICPR), 2024
[cn6]
Classification et estimation de densité de microstructures triplement périodiques avec des réseaux de neurones à convolution 3D
Manuel Ricardo Guevara Garban, Yves Chemisky, Prulière Étienne, Michaël Clément
Colloque National en Calcul des Structures (CSMA), 2024
[a4]
Deep learning assisted segmentation of CT-scanned ancient bones
Nicolas Vanderesse, Anthony Colombo, Michaël Clément, Nolan Bizon, Sharon Kuo, Timothy Ryan
Annual Meeting of the European Association of Archaeologists (EAA), 2024
[p2]
Superpixel segmentation: A long-lasting ill-posed problem
Rémi Giraud, Michaël Clément
Preprint arXiv:2411.06478, 2024

2023

[j7]
Deep grading for MRI-based differential diagnosis of Alzheimer's disease and Frontotemporal dementia
Huy-Dung Nguyen, Michaël Clément, Vincent Planche, Boris Mansencal, Pierrick Coupé
Artificial Intelligence in Medicine, 2023
[j6]
Towards better interpretable and generalizable AD detection using collective artificial intelligence
Huy-Dung Nguyen, Michaël Clément, Boris Mansencal, Pierrick Coupé
Computerized Medical Imaging and Graphics, 2023
[c12]
3D Transformer based on deformable patch location for differential diagnosis between Alzheimer’s disease and Frontotemporal dementia
Huy-Dung Nguyen, Michaël Clément, Boris Mansencal, Pierrick Coupé
MICCAI Workshop on Machine Learning in Medical Imaging (MLMI), 2023
[c11]
Diffusart: Enhancing line art colorization with conditional diffusion models
Hernan Carrillo, Michaël Clément, Aurélie Bugeau, Edgar Simo-Serra
CVPR Workshop on Computer Vision for Fashion, Art, and Design (CVFAD), 2023
[a3]
IA-SeReOs, an interdisciplinary project towards the automatic segmentation of CT-scanned ancient bone remains
Nicolas Vanderesse, Anthony Colombo, Nolan Bizon, Michaël Clément, Sharon Kuo, Timothy Ryan
International conference on artificIAl Intelligence and applied MAthematics for History and Archaeology (IAMAHA), 2023
[p1]
Exemplar-based image colorization using object-guided attention
Hernan Carrillo, Michaël Clément, Aurélie Bugeau
Preprint hal-04215100, 2023

2022

[b2]
Analysis of different losses for deep learning image colorization
Coloma Ballester, Aurélie Bugeau, Hernan Carrillo, Michaël Clément, Rémi Giraud, Lara Raad, Patricia Vitoria
Handbook of Mathematical Models and Algorithms in Computer Vision and Imaging, 2022
[b1]
Influence of color spaces for deep learning image colorization
Coloma Ballester, Aurélie Bugeau, Hernan Carrillo, Michaël Clément, Rémi Giraud, Lara Raad, Patricia Vitoria
Handbook of Mathematical Models and Algorithms in Computer Vision and Imaging, 2022
[c10]
Super-attention for exemplar-based image colorization
Hernan Carrillo, Michaël Clément, Aurélie Bugeau
Asian Conference on Computer Vision (ACCV), 2022
[c9]
Interpretable differential diagnosis for Alzheimer’s disease and frontotemporal dementia
Huy-Dung Nguyen, Michaël Clément, Boris Mansencal, Pierrick Coupé
International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI), 2022
[c8]
Non-local matching of superpixel-based deep features for color transfer
Hernan Carrillo, Michaël Clément, Aurélie Bugeau
International Conference on Computer Vision Theory and Applications (VISAPP), 2022

2021

[c7]
Deep grading based on collective artificial intelligence for AD diagnosis and prognosis
Huy-Dung Nguyen, Michaël Clément, Boris Mansencal, Pierrick Coupé
MICCAI Workshop on Interpretability of Machine Intelligence in Medical Image Computing (iMIMIC), 2021
[cn5]
Superpixel-based matching of high-resolution deep features for color transfer
Hernan Carrillo, Michaël Clément, Aurélie Bugeau
Journées francophones des jeunes chercheurs en vision par ordinateur (ORASIS), 2021

2020

[j5]
AssemblyNet: A large ensemble of CNNs for 3D whole brain MRI segmentation
Pierrick Coupé, Boris Mansencal, Michaël Clément, Rémi Giraud, Baudouin Denis de Senneville, Vinh-Thong Ta, Vincent Lepetit, José V. Manjón
NeuroImage, 2020
[j4]
Fuzzy directional enlacement landscapes for the evaluation of complex spatial relations
Michaël Clément, Camille Kurtz, Laurent Wendling
Pattern Recognition, 2020
[c6]
Enlacement and interlacement shape descriptors
Michaël Clément, Camille Kurtz, Laurent Wendling
International Conference on Pattern Recognition and Artificial Intelligence (ICPRAI), 2020
[cn4]
Algorithme de correspondance de superpatchs multi-échelles basé sur des descripteurs duals de superpixels
Rémi Giraud, Michaël Clément, Merlin Boyer
Congrès Reconnaissance des Formes, Image, Apprentissage et Perception (RFIAP), 2020

2019

[j3]
Multi-scale superpatch matching using dual superpixel descriptors
Rémi Giraud, Merlin Boyer, Michaël Clément
Pattern Recognition Letters, Special Issue on Hierarchical Representations, 2019
[c5]
AssemblyNet: A novel deep decision-making process for whole brain MRI segmentation
Pierrick Coupé, Boris Mansencal, Michaël Clément, Rémi Giraud, Baudouin Denis de Senneville, Vinh-Thong Ta, Vincent Lepetit, José V. Manjón
International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI), 2019
[a2]
Human and machine perception of three-dimensional shape from contour
James H. Elder, Yiming Qian, Michaël Clément, Srikumar Ramalingam
European Conference on Visual Perception (ECVP), 2019

2018

[j2]
Learning spatial relations and shapes for structural object description and scene recognition
Michaël Clément, Camille Kurtz, Laurent Wendling
Pattern Recognition, 2018
[a1]
What are the sparse components of 2D shapes?
Michaël Clément, James H. Elder
European Conference on Visual Perception (ECVP), 2018

2017

[phd]
Modélisation et apprentissage de relations spatiales pour la reconnaissance et l'interprétation d'images
Michaël Clément
Université Paris Descartes, 2017
[j1]
Directional enlacement histograms for the description of complex spatial configurations between objects
Michaël Clément, Adrien Poulenard, Camille Kurtz, Laurent Wendling
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2017
[c4]
Local enlacement histograms for historical drop caps style recognition
Michaël Clément, Mickaël Coustaty, Camille Kurtz, Laurent Wendling
International Conference on Document Analysis and Recognition (ICDAR), 2017
[c3]
Fuzzy directional enlacement landscapes
Michaël Clément, Camille Kurtz, Laurent Wendling
International Conference on Discrete Geometry for Computer Imagery (DGCI), 2017
[cn3]
Sacs de relations spatiales et de formes pour la reconnaissance d'images de scènes naturelles
Michaël Clément, Camille Kurtz, Laurent Wendling
Journées francophones des jeunes chercheurs en vision par ordinateur (ORASIS), 2017

2016

[jn1]
Description d'objets en couleurs à partir des relations spatiales entre régions structurelles
Michaël Clément, Camille Kurtz, Laurent Wendling
Revue des Nouvelles Technologies de l'Information, 2016
[c2]
Bags of spatial relations and shapes features for structural object description
Michaël Clément, Camille Kurtz, Laurent Wendling
International Conference on Pattern Recognition (ICPR), 2016
[cn2]
Descripteurs directionnels d'enlacement et d'entrelacement entre objets
Michaël Clément, Camille Kurtz, Laurent Wendling
Congrès national sur la Reconnaissance des Formes et l'Intelligence Artificielle (RFIA), 2016

2015

[c1]
Color object recognition based on spatial relations between image layers
Michaël Clément, Mickaël Garnier, Camille Kurtz, Laurent Wendling
International Conference on Computer Vision Theory and Applications (VISAPP), 2015
[cn1]
Descripteurs de relations spatiales entre régions structurelles pour la reconnaissance d'objets en couleurs
Michaël Clément, Camille Kurtz, Laurent Wendling
Atelier Fouille de Données Complexes (FDC), Conférence Internationale sur l'Extraction et la Gestion des Connaissances (EGC), 2015

International journals

[j10]
SpIRL: Spatially-aware image representation learning under the supervision of relative position descriptors
Logan Servant, Michaël Clément, Laurent Wendling, Camille Kurtz
Pattern Recognition, 2026
[j9]
Physics-informed graph neural networks to reconstruct local fields considering finite strain hyperelasticity
Manuel Ricardo Guevara Garban, Yves Chemisky, Michaël Clément, Étienne Prulière
International Journal for Numerical Methods in Engineering, 2025
[j8]
Brain Structure Ages — A new biomarker for multi-disease classification
Huy-Dung Nguyen, Michaël Clément, Boris Mansencal, Pierrick Coupé
Human Brain Mapping, 2024
[j7]
Deep grading for MRI-based differential diagnosis of Alzheimer's disease and Frontotemporal dementia
Huy-Dung Nguyen, Michaël Clément, Vincent Planche, Boris Mansencal, Pierrick Coupé
Artificial Intelligence in Medicine, 2023
[j6]
Towards better interpretable and generalizable AD detection using collective artificial intelligence
Huy-Dung Nguyen, Michaël Clément, Boris Mansencal, Pierrick Coupé
Computerized Medical Imaging and Graphics, 2023
[j5]
AssemblyNet: A large ensemble of CNNs for 3D whole brain MRI segmentation
Pierrick Coupé, Boris Mansencal, Michaël Clément, Rémi Giraud, Baudouin Denis de Senneville, Vinh-Thong Ta, Vincent Lepetit, José V. Manjón
NeuroImage, 2020
[j4]
Fuzzy directional enlacement landscapes for the evaluation of complex spatial relations
Michaël Clément, Camille Kurtz, Laurent Wendling
Pattern Recognition, 2020
[j3]
Multi-scale superpatch matching using dual superpixel descriptors
Rémi Giraud, Merlin Boyer, Michaël Clément
Pattern Recognition Letters, Special Issue on Hierarchical Representations, 2019
[j2]
Learning spatial relations and shapes for structural object description and scene recognition
Michaël Clément, Camille Kurtz, Laurent Wendling
Pattern Recognition, 2018
[j1]
Directional enlacement histograms for the description of complex spatial configurations between objects
Michaël Clément, Adrien Poulenard, Camille Kurtz, Laurent Wendling
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2017

International conferences or workshops

[c15]
Superpixel Anything: A general object-based framework for accurate yet regular superpixels
Julien Walther, Rémi Giraud, Michaël Clément
British Machine Vision Conference (BMVC), 2025
[c14]
Contrastive learning of image representations guided by spatial relations
Logan Servant, Michaël Clément, Laurent Wendling, Camille Kurtz
Winter Conference on Applications of Computer Vision (WACV), 2025
[c13]
Deep spherical superpixels
Rémi Giraud, Michaël Clément
International Conference on Pattern Recognition (ICPR), 2024
[c12]
3D Transformer based on deformable patch location for differential diagnosis between Alzheimer’s disease and Frontotemporal dementia
Huy-Dung Nguyen, Michaël Clément, Boris Mansencal, Pierrick Coupé
MICCAI Workshop on Machine Learning in Medical Imaging (MLMI), 2023
[c11]
Diffusart: Enhancing line art colorization with conditional diffusion models
Hernan Carrillo, Michaël Clément, Aurélie Bugeau, Edgar Simo-Serra
CVPR Workshop on Computer Vision for Fashion, Art, and Design (CVFAD), 2023
[c10]
Super-attention for exemplar-based image colorization
Hernan Carrillo, Michaël Clément, Aurélie Bugeau
Asian Conference on Computer Vision (ACCV), 2022
[c9]
Interpretable differential diagnosis for Alzheimer’s disease and frontotemporal dementia
Huy-Dung Nguyen, Michaël Clément, Boris Mansencal, Pierrick Coupé
International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI), 2022
[c8]
Non-local matching of superpixel-based deep features for color transfer
Hernan Carrillo, Michaël Clément, Aurélie Bugeau
International Conference on Computer Vision Theory and Applications (VISAPP), 2022
[c7]
Deep grading based on collective artificial intelligence for AD diagnosis and prognosis
Huy-Dung Nguyen, Michaël Clément, Boris Mansencal, Pierrick Coupé
MICCAI Workshop on Interpretability of Machine Intelligence in Medical Image Computing (iMIMIC), 2021
[c6]
Enlacement and interlacement shape descriptors
Michaël Clément, Camille Kurtz, Laurent Wendling
International Conference on Pattern Recognition and Artificial Intelligence (ICPRAI), 2020
[c5]
AssemblyNet: A novel deep decision-making process for whole brain MRI segmentation
Pierrick Coupé, Boris Mansencal, Michaël Clément, Rémi Giraud, Baudouin Denis de Senneville, Vinh-Thong Ta, Vincent Lepetit, José V. Manjón
International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI), 2019
[c4]
Local enlacement histograms for historical drop caps style recognition
Michaël Clément, Mickaël Coustaty, Camille Kurtz, Laurent Wendling
International Conference on Document Analysis and Recognition (ICDAR), 2017
[c3]
Fuzzy directional enlacement landscapes
Michaël Clément, Camille Kurtz, Laurent Wendling
International Conference on Discrete Geometry for Computer Imagery (DGCI), 2017
[c2]
Bags of spatial relations and shapes features for structural object description
Michaël Clément, Camille Kurtz, Laurent Wendling
International Conference on Pattern Recognition (ICPR), 2016
[c1]
Color object recognition based on spatial relations between image layers
Michaël Clément, Mickaël Garnier, Camille Kurtz, Laurent Wendling
International Conference on Computer Vision Theory and Applications (VISAPP), 2015

Book chapters

[b2]
Analysis of different losses for deep learning image colorization
Coloma Ballester, Aurélie Bugeau, Hernan Carrillo, Michaël Clément, Rémi Giraud, Lara Raad, Patricia Vitoria
Handbook of Mathematical Models and Algorithms in Computer Vision and Imaging, 2022
[b1]
Influence of color spaces for deep learning image colorization
Coloma Ballester, Aurélie Bugeau, Hernan Carrillo, Michaël Clément, Rémi Giraud, Lara Raad, Patricia Vitoria
Handbook of Mathematical Models and Algorithms in Computer Vision and Imaging, 2022

Abstracts or communications

[a5]
Fouille virtuelle d’urnes funéraires assistée par IA: une étude de cas
Nicolas Vanderesse, Michaël Clément, Romane Martin, Stéphane Rottier
IA et innovations numériques : usages et enjeux en archéologie, 2025
[a4]
Deep learning assisted segmentation of CT-scanned ancient bones
Nicolas Vanderesse, Anthony Colombo, Michaël Clément, Nolan Bizon, Sharon Kuo, Timothy Ryan
Annual Meeting of the European Association of Archaeologists (EAA), 2024
[a3]
IA-SeReOs, an interdisciplinary project towards the automatic segmentation of CT-scanned ancient bone remains
Nicolas Vanderesse, Anthony Colombo, Nolan Bizon, Michaël Clément, Sharon Kuo, Timothy Ryan
International conference on artificIAl Intelligence and applied MAthematics for History and Archaeology (IAMAHA), 2023
[a2]
Human and machine perception of three-dimensional shape from contour
James H. Elder, Yiming Qian, Michaël Clément, Srikumar Ramalingam
European Conference on Visual Perception (ECVP), 2019
[a1]
What are the sparse components of 2D shapes?
Michaël Clément, James H. Elder
European Conference on Visual Perception (ECVP), 2018

Preprints

[p2]
Superpixel segmentation: A long-lasting ill-posed problem
Rémi Giraud, Michaël Clément
Preprint arXiv:2411.06478, 2024
[p1]
Exemplar-based image colorization using object-guided attention
Hernan Carrillo, Michaël Clément, Aurélie Bugeau
Preprint hal-04215100, 2023

National journals

[jn1]
Description d'objets en couleurs à partir des relations spatiales entre régions structurelles
Michaël Clément, Camille Kurtz, Laurent Wendling
Revue des Nouvelles Technologies de l'Information, 2016

National conferences

[cn8]
Réseaux de neurones par graphes informés par la physique pour la reconstruction de champs de contraintes mécaniques
Manuel Ricardo Guevara Garban, Yves Chemisky, Michaël Clément, Prulière Étienne
Journées francophones des jeunes chercheurs en vision par ordinateur (ORASIS), 2025
[cn7]
Apprentissage contrastif de représentations d'images guidée par les relations spatiales
Logan Servant, Michaël Clément, Laurent Wendling, Camille Kurtz
Journées francophones des jeunes chercheurs en vision par ordinateur (ORASIS), 2025
[cn6]
Classification et estimation de densité de microstructures triplement périodiques avec des réseaux de neurones à convolution 3D
Manuel Ricardo Guevara Garban, Yves Chemisky, Prulière Étienne, Michaël Clément
Colloque National en Calcul des Structures (CSMA), 2024
[cn5]
Superpixel-based matching of high-resolution deep features for color transfer
Hernan Carrillo, Michaël Clément, Aurélie Bugeau
Journées francophones des jeunes chercheurs en vision par ordinateur (ORASIS), 2021
[cn4]
Algorithme de correspondance de superpatchs multi-échelles basé sur des descripteurs duals de superpixels
Rémi Giraud, Michaël Clément, Merlin Boyer
Congrès Reconnaissance des Formes, Image, Apprentissage et Perception (RFIAP), 2020
[cn3]
Sacs de relations spatiales et de formes pour la reconnaissance d'images de scènes naturelles
Michaël Clément, Camille Kurtz, Laurent Wendling
Journées francophones des jeunes chercheurs en vision par ordinateur (ORASIS), 2017
[cn2]
Descripteurs directionnels d'enlacement et d'entrelacement entre objets
Michaël Clément, Camille Kurtz, Laurent Wendling
Congrès national sur la Reconnaissance des Formes et l'Intelligence Artificielle (RFIA), 2016
[cn1]
Descripteurs de relations spatiales entre régions structurelles pour la reconnaissance d'objets en couleurs
Michaël Clément, Camille Kurtz, Laurent Wendling
Atelier Fouille de Données Complexes (FDC), Conférence Internationale sur l'Extraction et la Gestion des Connaissances (EGC), 2015

PhD Thesis

[phd]
Modélisation et apprentissage de relations spatiales pour la reconnaissance et l'interprétation d'images
Michaël Clément
Université Paris Descartes, 2017

Students

PhD students

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

Master students

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

Projects

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)

Teaching

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.

Current courses

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)

Past courses

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