Current focuses:

• Label-efficient learning

• Representation learning                

• Self-supervised/Weakly-supervised learning

• Few-shot learning

• Multi-task learning

• Knowledge distillation

• Federated learning

• Vision and EO tasks: classification, object detection, super-resolution

Research interests:

• Computer vision, image analysis and processing                     

• Machine learning, deep learning     

• Signal and image processing on graphs

• Morphological mathematics  on images   

• Hierarchical learning and structured classification

• Remote sensing data fusion (optical, radar, lidar, sonar)

• Remote sensing applications (detection, segmentation, super-resolution)           

Research projects:

-----On-going---

• AXOLOTL (2024-2027) - Role: Partner's Lead

  • From sky to seafloor observation: Achieving excellence in oceanic surveillance and conservation through deep learning.

  • Funding: 1.5 M€, HORIZON  EUROPE

  • Consortium: CMMI Cyprus (main PI), UBS France and VLIZ Belgium

• ROMMEO (2022-2024) - Principal Investigator

  • Robust multitask learning via mutual knowledge distillation for earth observation 

  • Funding: 63k€, Région Bretagne (France)

• OTTOPIA (2021-2024)

  • Earth observation by optimal transport for artificial intelligence

  • Funding: 467k€, ANR

-----Past Projects----

• OWFSOMM (2020-2023)

  • Offshore wind farm surveys of marine megafauna: standardization of tools and methods for monitoring at OWF scales 

  • Funding: 529K€, ANR/FEM

• SEMMACAPE (2019-2023)

  • Monitoring and study of marine megafauna by automatic characterization in wind farms

  • Funding: 128k€, ADEME

• ANR MULTISCALE (2019-2023)

  • Multi-variate, -temporal, -resolution and -source remote sensing image analysis and learning 

• ANR DEEPDETECT (2018-2020)

  • Detection and recognition of multiple objects on variable backgrounds by deep learning

• R&T CNES CARS (2018-2019)

  • Vehicle counting by deep learning from Pléiades images

• DELORA (2016-2018) 

  • Augmented reality detection and relocation of buried networks

Editorial/Expertise:

• Expertises

  • Member of Editorial Board  of Digital Signal Processing, Elsevier (since 2022)

  • Evaluation member of CE23 – Intelligence Artificielle », ANR Appel à projets générique 2021.

  • Mentor and Evaluator of IT Swin Hackaton 2023 (Proptech/EduTech/HealthTech), Swinburne University.

  • Applied Research Specialist at VinAI Research (2020-2021)

• Member of PhD Committee (Jury de thèse)

  • Sara Akodad, Université de Bordeaux, IMS Lab. PhD topic : « Ensemble learning methods on the space of covariance matrices : application to remote sensing scene and multivariate time series classification ». defended on 08/11/2021

• Member of Individual PhD Mornitoring Committee (Comité de suivi individuel, CSI)

  • Kévin Planolles, Université Montpellier, LIRMM Lab. PhD topic : « automated monitoring of fish biodiversity with work on detection algorithms », started 09/2022.

  • Shuo Yang, CY Cergy Paris Université. PhD topic : « Graph neural networks for human pose estimation »,  started 05/2023.

• Guest Editor

  • Special issue on Machine learning for earth observation data, Machine Learning, with Thomas Corpetti (LETG-Rennes UMR 6554, Rennes), Dino Ienco (INRAE, UMR TETIS, Montpellier), Sébastien Lefèvre (IRISA, UMR 6074, Vannes) et Roberto Interdonato (INRAE, UMR TETIS, Montpellier). 

  • Special issue on Feature-based methods for remote sensing image classification, Remote Sensing, with Carlos Lopez-Martinez (Universitat Politècnica de Catalunya, Espagne) et Pelich Ramona (Luxembourg Institute of Science and Technology, Luxembourg).

• Co-chair of the MACLEAN (Machine learning for Earth Observation) workshop at ECML/PKDD, annually since 2019.

• Co-chair of the MACLEAN session at GDR MADICS  (2019-2022)