Simon Madec is a research scientist based in France with eight years of experience applying deep learning and multi-source remote sensing to agricultural and environmental problems. Currently at CIRAD, he develops computer vision methods for high-resolution crop phenotyping, combining multispectral and RGB imagery to retrieve biophysical variables from aerial and satellite platforms. His background spans PhD-level image analysis and signal processing from Grenoble INP and INRA, plus hands-on engineering experience in drone imaging, solar forecasting, and real-time video processing. Known for bridging theory and field-ready solutions, he prototypes end-to-end pipelines that translate optical flow, CNNs and multisensor fusion into actionable plant stress metrics for researchers and agronomists.
8 years of coding experience
7 years of employment as a software developer
Engineer's degree, Computer vision & science, signal processing, Engineer's degree, Computer vision & science, signal processing at Grenoble INP Phelma
PHD, Image analysis, statistics, deep learning, field crop phenotyping, PHD, Image analysis, statistics, deep learning, field crop phenotyping at INRA
Classe préparatoire PCSI/PSI, Maths, Physics & Engineering Science, Classe préparatoire PCSI/PSI, Maths, Physics & Engineering Science at Lycée Chateaubriand
Contributions:9 commits, 8 pushes, 1 comment in 3 years 1 month
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