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Water-R2O: National Science Foundation Research Traineeship (NRT)

Saide Zand

Photo of Saide Zand

Department: Department of Civil, Construction and Environmental Engineering  

Degree: Doctorate

Year in Program: 1st

I am a first-year PhD student at the Coastal Hydrology Lab at the University of Alabama. My research is focused on applying Machine Learning (ML) in hydrology and coastal flood mapping. My current research uses Physics-Informed Neural Networks (PINN) to predict coastal flood extent and depth. Specifically, I focus on integrating fundamental physical equations, such as shallow water equations, into ML models to improve flood inundation predictions. I use the Delft-3D model to generate data for my Convolutional Neural Network (CNN) model across different scenarios. I am dedicated to advancing flood prediction methods to protect coastal communities better.