Today we’re speaking with Professor Alex Rodriguez, an assistant professor of computer science and engineering at the University of Michigan. Prof. Rodriguez’s research sits at the intersection of machine learning, time series analysis, multi-agent systems, and uncertainty quantification, particularly in forecasting complex phenomena such as epidemics and natural disasters. In this episode, we explore how AI can inform decision-making during public health crises, strengthen preparedness for natural disasters, and bridge the gap between data-driven models and real-world policy. Key points include the challenges posed by uncertainty, the need to adapt models to unpredictable situations, and the importance of cross-disciplinary collaboration.

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