Summary
Noemi Vergopolan is a computational hydrologist and engineer with nine years of experience developing high-resolution, scalable hydrological prediction systems that fuse satellite remote sensing, land surface modeling, machine learning, and high-performance computing. Her work—spanning Princeton, NOAA GFDL, and soon Rice University—focuses on actionable hydrological information for monitoring and forecasting droughts, floods, and water scarcity at local scales. She led the development of SMAP-HydroBlocks, producing the first 30-meter surface soil moisture dataset for the United States, and helped create NOAA’s inaugural satellite land data assimilation system integrating in-situ and satellite observations. Trained at Princeton and with field and consulting experience in Brazil and at JPL, she brings both rigorous academic methods and hands-on applied engineering to water-climate challenges. Her research group will recruit PhD students and postdocs interested in computational hydrology and remote sensing, emphasizing reproducible, production-ready modeling for decision support.
9 years of coding experience
12 years of employment as a software developer
Oxford’s Smith School of Enterprise and the Environment Summer Program, Oxford’s Smith School of Enterprise and the Environment Summer Program at University of Oxford
B.S Civil and Environmental Engineering, B.S Civil and Environmental Engineering at North Carolina State University
Bachelor's Degree Environmental Engineering, Bachelor's Degree Environmental Engineering at Universidade Federal do Paraná
Doctor of Philosophy (Ph.D.) Environmental and Water Resources Engineering, Doctor of Philosophy (Ph.D.) Environmental and Water Resources Engineering at Princeton University
Spanish, Portuguese, English