Mathieu Gravey is a PhD candidate in geoscience at the University of Lausanne with nine years of experience developing high-performance image processing and geostatistical methods for satellite data. He specializes in spectral enhancement of historical satellite imagery and created Quantile Sampling, a multiple-point statistic algorithm optimized for modern architectures (C/C++/OpenMP/OpenCL) with Python, MATLAB and R interfaces. His work blends theoretical geostatistics with practical system engineering—ranging from CUDA-accelerated simulated annealing for multi-sensor calibration to OpenCV/OpenCL 3D reconstruction and Qt/OpenGL visualization. Recognized with the Intel Modern Code Developer Challenge grand prize in 2015, he combines HPC expertise with a strong background in embedded and mobile imaging prototypes. Based in Basel, he brings both academic rigor and production-ready open-source implementations that make complex spectral-unification techniques accessible to practitioners.
9 years of coding experience
BAc +2 (CPGE), Mathématiques, physique et informatique, BAc +2 (CPGE), Mathématiques, physique et informatique at Lycée Albert Schweitzer
Brevet, Brevet at Collège Des Missions
BAC S SVT, BAC S SVT at Lycée Louis Armand
Ingénieur diplômé de l'Ecole nationale supérieure des mines d'Alès, Ingénierie informatique, Ingénieur diplômé de l'Ecole nationale supérieure des mines d'Alès, Ingénierie informatique at Ecole des Mines d'Alès
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Mathieu Gravey - PhD. Student at UNIL - Université de Lausanne