Elias Prado is a research geologist and machine-learning practitioner with eight years at the Geological Survey of Brazil, where he coordinates applied geoscience research to deliver AI-driven solutions for mineral and energy exploration. He holds a PhD from Unicamp and a master's focused on reflectance spectroscopy and economic geology, combining deep domain knowledge with practical skills in Python, TensorFlow/PyTorch, and full‑stack tools (ReactJS + Flask). His work spans mineral prospectivity mapping, hyperspectral data processing, geophysical and remote-sensing analysis, and he has translated those research pipelines into deployable software. Notably, he blends classical geological mapping experience with advanced deep learning and reinforcement learning training from Udacity, enabling novel approaches to target identification in complex terrains. Based in Cruzeiro, Brazil, Elias bridges field geology and production-ready data science to accelerate discovery in mining, oil & gas, and geothermal sectors.
8 years of coding experience
Curso, Reinforcement Learning, Curso, Reinforcement Learning at Udacity
nível avançado em Língua Inglesa, Língua Inglesa, nível avançado em Língua Inglesa, Língua Inglesa at Casa Thomas Jefferson
Curso, Deep Learning, Curso, Deep Learning at Udacity Brasil
Doctor of Philosophy - PhD, Geological and Earth Sciences/Geosciences, Doctor of Philosophy - PhD, Geological and Earth Sciences/Geosciences at Universidade Estadual de Campinas
Master's degree, Caracterização Espectral do Depósito de Ferro N4WS, Carajás, Brasil, Master's degree, Caracterização Espectral do Depósito de Ferro N4WS, Carajás, Brasil at Universidade de Brasília
Pós-doutorado, Geological and Earth Sciences/Geosciences, Pós-doutorado, Geological and Earth Sciences/Geosciences at Universidade Federal de Santa Catarina
Contributions:1 release, 111 commits, 2 PRs in 4 years 4 months
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