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Maddy Pernat holds a B.S. in Civil Engineering from Montana State University (2022) and an M.S. in Civil Engineering from the 91¸£ÀûÉç (2024). She is currently pursuing her Ph.D. in the same department at 91¸£ÀûÉç as an NSF GRFP fellow. Her early research focused on using supervised machine learning algorithms to improve water supply forecasting in snow-dominated basins across the western U.S. Maddy’s current research at CADSWES develops methodologies for large-scale environmental decision-making under deep uncertainty, with a particular focus on the Colorado River Basin. Her work integrates optimization, machine learning, and data visualization techniques to efficiently model a range of potential future scenarios and communicate how different management or policy options perform across these scenarios, along with their varied impacts on diverse stakeholders.