About me

I am an Assistant Professor (maitre de conférences in French) in computer science at AgroParisTech in the MIA Paris-Saclay lab. I am interested in machine learning for environmental sciences. Currently, I focus on multimodal and multisource representation learning, with applications to the monitoring of industrial pollution and wildfire simulation.

Previously, I was a postdoctoral research fellow at CNES in collaboration with the SPE lab from CNRS - Corsica University. I completed my PhD (manuscript) at ONERA, Magellium and ISAE-SUPAERO in close collaboration with the Toulouse Mathematics Institute on the semantic segmentation of airborne hyperspectral images for mapping impermeable surfaces in large urban areas.

I try to conduct my research following the principles of Slow Science and Open Science. I also attempt to limit the carbon footprint of my research, and I therefore do not travel by plane to attend conferences.

News

November 2026: Léo Paillet has joined our team in MIA Paris Saclay for a 2-year postdoc position on multimodality in remote sensing with applications in agricultural monitoring, in collaboration with Jean-Baptiste Féret, Cássio Fraga Dantas and Florian De Boissieu! The postdoc is funded by the PEPR Agroécologie et Numérique.

October 2026: Congrats to Marius Charles who started his PhD about disentanglement learning for transfer learning with applications to the simulation of bio-production, co-supervised with Alberto Tonda, Vincent Guigue and me! The PhD is funded by the project MuSiHC within the PEPR B-BEST.

June 2025: Our papers introducing DEFLECT and p3VAE have been accepted to ICCV 2025 and Springer Machine Learning, respectively!

Selected publications

Prediction losses VS alignment loss Can multimodal representation learning by alignment preserve modality-specific information?
R. Thoreau, J. Levillain and D. Derksen

MACLEAN workshop @ ECML-PKDD 2025.

[arXiv] [code] [slides]

DEFLECT performance Parameter-Efficient Adaptation of Geospatial Foundation Models through Embedding Deflection
R. Thoreau*, V. Marsocci* and D. Derksen (*Equal contribution)

IEEE/CVF International Conference on Computer Vision (ICCV) 2025.

[paper] [arXiv] [code] [poster] [video]

p3VAE archirecure Physics-informed Variational Autoencoders for Improved Robustness to Environmental Factors of Variation
R. Thoreau, L. Risser, V. Achard, B. Berthelot and X. Briottet

Springer Machine Learning.

[paper] [arXiv] [code] [slides]

Data sets comparison Toulouse Hyperspectral Data Set: a benchmark data set to assess semi-supervised spectral representation learning and pixel-wise classification techniques
R. Thoreau, L. Risser, V. Achard, B. Berthelot and X. Briottet

ISPRS Journal of Photogrammetry and Remote Sensing.

[paper] [data set] [code] [arXiv]

AL strategies Active Learning for Hyperspectral Image Classification: a Comparative Review
R. Thoreau, V. Achard, L. Risser, B. Berthelot and X. Briottet

IEEE Geoscience and Remote Sensing Magazine.

[paper] [code]

Teaching

Current courses

I teach computer science (programming with Python / SQL, machine learning, and deep learning for image analysis) to undergraduate and graduate students at AgroParisTech. I am also involved, as a non-expert, in classes of ethics, history and philosophy of sciences.

Past courses (2020 - 2025)
  • Machine learning (lectures) at Paul Sabatier University, M1 MAPI3,
  • Introduction to machine learning (lectures) at Paul Sabatier University, 3rd year BS in Mathematics / Computer Science,
  • Introduction to statistics (lectures) at Paul Sabatier University, 2nd year BS in Biochemistry,
  • Integration and probability theory (tutorials) at ENSEEIHT engineering school,
  • Statistical foundations of Machine Learning (practical works) at ISAE-SUPAERO, Data & Decision Sciences MS,
  • Combinatorial optimization (practical works) at Paul Sabatier University, Computer Science MS,
  • Algorithmic (practical works) at Paul Sabatier University, Computer Science BS,
  • Introduction to python (practical works) at Paul Sabatier University, Civil Engineering BS.

Student supervision

  • April to October 2025, Hugo André, final-year student at ISAE-SUPAERO on deep generative modeling for the inversion of industrial stack plumes from satellite images, in collaboration with Pierre-Yves Foucher (ONERA), Camille Desjardins, Laura Le Barbier and Solange Lemai-Chenevier (CNES).
  • March to August 2023, Arthur Cassou, final-year student at ENSTA Bretagne on the integration of physical priors in generative models for hyperspectral data, in collaboration with Laurent Risser, Véronique Achard and Xavier Briottet.
  • May to July 2022, Gaspard Loupit, second-year student at ISAE-SUPAERO on the comparison of features extracted by spatial-spectral convolutions to morphological profiles through LIME explanations for hyperspectral images, in collaboration with Véronique Achard.
  • April to July 2022, Clément Lefranc, master student in computer science at Paul Sabatier University on the development of a QGIS plug-in for active learning on Earth observation data, namely AL4EO.

MILO scientific seminars

MILO seminars are scientific seminars about mathematics and computing, e.g. machine learning, applied or applicable to Earth observation. I've been organizing the seminars since May 2024 within the COMET Signal and Image Processing community, a community of experts initiated by CNES, the French spatial agency, in order to gather academic researchers and engineers from the space industry in France. If you would like to present your work, please reach out!