Information
📚 Organization | Université de Bordeaux |
📆 Period @ ESA Φ-lab | November, 2026 – November, 2027 |
🌍 Project @ ESA CIN | Statistical method for hyperspectral unmixing on CHIME Data |
🔨 Linkedin | |
📝 Publications | H. Jeannin, F. Bouchard, P. Vallet, G. Ginolhac, and A. Giremus, "On the Endmembers Detection for Hyperspectral Imaging in the High-Dimensional Regime," 2025 33rd European Signal Processing Conference |
Bio
I am Hugo Jeannin, a PhD candidate at Université de Bordeaux. My research focuses on statistical methods for analyzing hyperspectral data, with particular emphasis on high-dimensional statistics and random matrix theory. I am especially interested in developing methods that are both theoretically grounded and applicable to complex, large-scale Earth Observation data.
Current Role
My work explores statistical approaches to hyperspectral image analysis, particularly spectral unmixing. Spectral unmixing aims to identify the spectral signatures of the materials present in an image and estimate their relative proportions within each pixel. My objective is to develop methods capable of jointly estimating spectral signatures, abundance maps, reconstruction residuals, and the uncertainty associated with these quantities.
Areas of Expertise
My expertise lies at the intersection of statistical signal processing, high-dimensional statistics, random matrix theory, hyperspectral imaging, and Earth Observation. These areas allow me to investigate how statistically principled and physically interpretable methods can complement modern machine-learning models.
Vision for the Future
My long-term objective is to contribute to the development of reliable, interpretable, and transferable methods for analyzing complex Earth Observation data.
Project as CIN Researcher
Coming Soon