I am a research scientist who designs data-driven techniques for visual understanding at ESA/ESRIN and more precisely in the Φ-lab, which explores innovative technologies to accelerate and transform Earth observation.

My work is at the crossroads of statistics, machine learning, image processing, computer vision, and now quantum computing. I am interested in tackling practical problems that arise in Earth observation, to bring solutions to current environment and population challenges.

I am an Associate Editor of the Geoscience and Remote Sensing Letters. I co-organise the CVPR Earth Vision worskhop series (current edition: CVPR’2023/EarthVision’23 workshop) and the ESA-ECMWF Machine Learning for Earth System Observation and Prediction workshop series (last year’s edition: ML4ESOP’2022).

In earlier times, I did my PhD at with INRIA/Imedia team and University of Versailles, near Paris, France. I also spent some time at CNR / Istituto di Scienza e Tecnologie dell’Informazione (ISTI) in Pisa, Italy, at University of Bern / Institut für Informatik in Bern, Switzerland, and at ENS Paris Saclay (was Cachan) / Centre des Mathématiques et de Leurs Applications (CMLA). From 2008 to 2020, I was a research scientist at ONERA, the French aerospace laboratory, near Paris, France, developing machine learning and computer vision for multimedia, robotics and Earth observation. In 2019, I obtained my Habilitation (HDR) from University Paris-Saclay.

I used to teach regularly at University Paris Dauphine (Algorithms, from 2001 to 2003) and École Polytechnique (Computer Vision Lab, from 2011 to 2017), among other venues. From 2016 to 2020, I taught Machine Learning and Computer Vision at Institut d’Optique Graduate School (Univ. Paris Saclay) and ENSTA ParisTech (Institut Polytechnique de Paris). I also gave tutorials on (Deep) Machine Learning at JURSE’2019 and IGARSS’2019, and continual formation including on-line courses at EuroSDR / Eduserv.

I served as Chair of the IEEE GRSS Image Analysis and Data Fusion Technical Committee from 2017 to 2019, and previously as co-chair from 2015 to 2017. One of our main activities was to organize the Data Fusion Contest, an annual competition for multimodal Earth observation.

I am/was a co-organizer of:

• the Dagstuhl seminar on “Space and Artificial Intelligence” in November 2023,
• the Big Data from Space (BiDS) 2023 conference,
• the AI for Humanitarian Assistance and Disaster Response Workshop (AI+HADR) 2023 workshop at ICCV’2023,
• the ESA 6th Quantum Technology Conference in 2023,
• the Earth Vision workshop series, computer vision meets Earth observation: CVPR’19/EarthVision workshop’19, CVPR’20/EarthVision workshop’20, CVPR’2021/EarthVision’21 workshop, CVPR’2022/EarthVision’22 workshop, and CVPR’2023/EarthVision’23 workshop,
• the NeurIPS 2022 competition Weather4Cast on forecasting rain events from satellite data.
• the ESA - ECMWF workshops on Machine Learning for Earth System Observation and Prediction, 2020 edition, 2021 edition, and 2022 edition,
• the ICIP 2022 Grand Challenge Hyperview on Seeing beyond the visible: Estimating soil parameters from hyperspectral images,
• the IEEE GRSS Data Fusion Contest 2022,
• the ESA 5th Quantum Technology Conference in 2021,
• The ECML/PKDD Discovery Challenge Mysteries of the Mayas for cultural heritage with remote sensing,
• the 2nd conference on “Space and AI” co-located with ECML-PKDD’21 with CLAIRE AI society,
• the ESA - ELLIS society 2021 Workshop on Quantum Algorithms and Machine Learning for Huge Data Analysis, Simulation and Potential Earth Observation Applications,
• the IEEE GRSS Data Fusion Contests in 2016 (results), 2017 (results), 2018 (results), 2019 (results).
• the RFIAP’18/TerraData workshop,

I have been guest editor for:

• 2018/2019 Geoscience and Remote Sensing Letters special stream on Advanced Processing for Multimodal Optical Remote Sensing Imagery.
• 2019/2020 J. of Selected Topics in Applied Earth Observation and Remote Sensing (JSTARS) for the special issue about “Computer Vision-based Approaches for Earth Observation”
• 2021/2022 J. of Selected Topics in Applied Earth Observation and Remote Sensing (JSTARS) for the special issue about “Quantum resources for Earth Observation”