Jorge Bravo
Graduate Research Assistant
Hoboken, New Jersey, United States
Summary
👤
Senior🎓
Top SchoolJorge Bravo is a PhD candidate and applied researcher with eight years of experience implementing operational meteorological and hydrological models (WRF, MPAS, WRF-Hydro) and deploying large geospatial datasets in formats from GRIB/NetCDF/HDF to Zarr and COGs. Based in Hoboken and active at Stevens Institute of Technology and iSMART Lab, he blends hands-on model deployment with remote-sensing analysis using GOES-R, SPOT and GeoEye to study coastal change and beach loss. He has practical experience moving research into operations—running forecast systems, producing climate bulletins, and supporting decision-making for civil protection agencies. A contributor to the popular Satpy project, he improved natural color compositing and image-processing routines that enhance satellite data visualization. Fluent in Python and geospatial tools (QGIS, SNAP, GEE), he pairs strong scientific foundations in hydrometeorology with production-focused data engineering skills that bridge academic research and operational forecasting.
8 years of coding experience
Licenciatura, Ciencias Atmosfericas, Licenciatura, Ciencias Atmosfericas at Universidad VeracruzanaDoctor of Philosophy - PhD, Civil Engineering, Doctor of Philosophy - PhD, Civil Engineering at Stevens Institute of TechnologyMaestría, Hydrometeorología, Maestría, Hydrometeorología at Universidad de Guadalajara
Github Skills (8)
data-preprocessing10
xray10
satellite-data10
python10
data-processing10
xa10
data-analysis9
weather8
Programming languages (2)
Github contributions (5)
pytroll/satpy
Dec 2018 - Jul 2020
Python package for earth-observing satellite data processing
Role in this project:
Back-end Developer
Back-end DeveloperContributions:6 reviews, 45 commits, 14 PRs in 1 year 7 months
Contributions summary:Jorge contributed to the `satpy` project, a Python package for processing earth-observing satellite data. Their work focused on enhancing the "natura color" composite functionality, which included modifying existing compositing classes, adding new compositing classes, and testing the new color enhancement algorithms. These changes involved modifying data handling and image processing routines within the `satpy/composites` directory. This indicates a focus on improving the visual representation and analysis capabilities of the satellite data.
satellite-imagerypythonsatellitedata-processingearth
jhbravo/CVjorgeb
Mar 2018 - Sep 2021
Contributions:20 commits, 18 pushes, 1 branch in 3 years 6 months
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