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My primary field of study is hydrological modeling for flood forecasting using observations from remote sensing platforms with a focus on model development, probabilistic forecasting and data assimilation. I am one of the main developers of the suite of new generation tools for flash flood forecasting in the FLASH system. My work for FLASH has been on parameter estimation and uncertainty characterization using multi-dimensional strategies based on machine-learning algorithms. More recently, I have worked on the development of impact-specific flash flood products and ensemble techniques that address quantitative precipitation forecasts biases. Additionally, I am studying the application of hydraulic geometry relationships to improve the representation in hydrologic models of physical processes involved in stream flows and inundation.