I am a computational hydrologist, engineer, and scientist working on solutions for water resources and climate. My research aims to aid actionable decision-making by improving hydrological information for monitoring and forecasting hydrological extremes and their impacts at the local scales. To this end, I develop scalable computational approaches for high-resolution hydrological prediction by leveraging advances in satellite remote sensing, land surface modeling, machine learning, data fusion, and high-performance computing.
I hold a PhD in Civil and Environmental Engineering from Princeton University, working with Prof. Eric Wood and Justin Sheffield. Currently, I am a postdoctoral research associate in the Atmospheric and Ocean Science Program at Princeton University and the NOAA Geophysical Fluid Dynamics Laboratory working with Dr. Elena Shevliakova on Earth System Modeling and satellite land data assimilation. Prior, I worked on water resources and environmental engineering consulting.
For my contribution to science, I was awarded the 2022 Paul F. Boulos Excellence in Computational Hydrology Award by the American Academy of Environmental Engineers and Scientists and the 2022 AGU Science for Solutions Award for “outstanding contributions to water and food security through advances in hyper-resolution land surface modeling and satellite remote sensing”.
Learn more about my interests in research and publications, and by following my updates on Twitter.
PhD in Civil & Environmental Engineering
Princeton University, 2021
Statistics & Machine Learning Certificate
Princeton University, 2021
Computational Science & Engineering Certificate
Princeton University, 2019
MA in Civil & Environmental Engineering
Princeton University, 2017
BS Environmental Engineering
Federal University of Paraná, 2014
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