Nicolas Audebert

Nicolas Audebert is a Computer Vision and Machine Learning researcher working as a junior research director at the French National Institute of Geographic and Forest Information (IGN) in the LASTIG laboratory, STRUDEL team. He is currently on leave from his position as Associate Professor of Computer Science at the Conservatoire national des arts et métiers (Cnam) where he was part of the Vertigo team. His research spans computer vision, machine learning, and Earth Observation with applications in remote sensing and video games.

Dr. Audebert earned his PhD in Computer Science from ONERA and IRISA in 2018, followed by an MEng in Computer Science from Supélec and an MSc in Human-Computer Interaction from Université Paris-Sud in 2015. In May 2025, he successfully defended his habilitation à diriger des recherches (HDR) titled "Learning representations from observations".

His research focuses on representation learning, where he develops methods to create abstract representations of raw data that allow computers to manipulate high-level concepts numerically. In Earth Observation, he processes and makes sense of large volumes of satellite data for land cover mapping, change detection, and image interpretation. His work in machine learning for games explores how to use reinforcement learning to generate diverse and challenging AI in video games. Additional research interests include generative models, multimodal learning, and domain adaptation techniques.

His recent publications demonstrate expertise in cross-sensor learning, super-resolution of satellite imagery, diffusion models for Earth Observation, and robust image retrieval systems. His work bridges theoretical advances in deep learning with practical applications in geospatial analysis, with a particular focus on developing methods that work across different sensor types and environmental conditions.

• Outstanding Reviewer for ECCV 2024
• Outstanding Reviewer for BMVC 2021
• Outstanding Reviewer for ICCV 2021
• Best Benchmarking Contribution Award at GEOBIA 2016
• 2nd best student paper award at JURSE 2017
• Google Research Scholar Program gift

Dr. Audebert currently advises four PhD students: Maxime Merizette (semantic segmentation of 3D point clouds), Georges Le Bellier (domain adaptation for Earth Observation), Léo Géré (generative models for music), and Aimi Okabayashi (super-resolution of satellite image time series). He has successfully supervised two PhD students to completion: Perla Doubinsky (controlling generative models) and Elias Ramzi (robust image retrieval), whose thesis won the AFRIF PhD award 2024. He has mentored numerous MSc students on diverse topics including flood detection, procedural generation of video game levels, and deep learning for communication systems.

He leads the MAGE project (2022-2026), funded by the Agence Nationale de la Recherche, which investigates using procedural generation and modern rendering engines to create labeled synthetic data for Earth Observation models, particularly for disaster mapping applications. He also leads the SESURE project (2021-2023) focused on super-resolution of Sentinel-2 time series, and previously led the RL-Games project (2020-2022) exploring reinforcement learning applications for video games.