Matthieu Puigt

Matthieu Puigt is a Professor at Université du Littoral Côte d'Opale, specializing in signal and image processing with a focus on statistical machine learning, low-rank approximations, and sparse component analysis. His research extends to hyperspectral data fusion, unmixing, and restoration, as well as applications in chemistry and computational imaging. He leads the SPECIFI research team.

• Research Themes: Blind source separation, compressive learning, sensor calibration, and big data analysis
• Applications: Audio signal processing, environmental monitoring via drones, and urban air quality assessment

His recent work includes developing VAE-based hyperspectral image emulators, tensor decomposition methods for multisensor data, and frameworks for butterfly species recognition. He advised Valentin Mullet's 2022 thesis on blockchain traceability systems and actively contributes to IEEE and GRETSI conferences.