Felipe has worked on projects related to hydrological baselines, numerical modeling focused on flood studies and hydrological modeling applied to climate change, water balance studies oriented toward environmental sustainability, and the design of hydraulic works such as water pressurization systems, contour channels, and river defenses.
He has solid knowledge of programming and database automation, as well as Geographic Information Systems (GIS), excelling in the processing of multispectral, hyperspectral, and SAR radar satellite images to obtain classifications or regressions using machine learning techniques.
In addition, Felipe specializes in a variety of numerical modeling software, including HEC-RAS, GR4J, WEAP, Allievi, and EPANET, and has advanced skills in programming languages such as R, Python, and JavaScript.
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