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Explore a 56-minute seminar from the Paul G. Allen School's AI series featuring Daniel Sheldon on leveraging big data and algorithms for ecological research and conservation efforts. Delve into novel approaches for understanding large-scale ecological phenomena, such as bird migration, using data from sensor networks and citizen scientists. Learn about collective graphical models for efficient reasoning with aggregate data, applicable to both bird migration and human mobility studies. Discover the stochastic network design framework and its applications in spatial conservation planning, optimizing dam removal, and enhancing road network resilience. Gain insights into how these algorithmic frameworks can revolutionize ecology and conservation practices in the face of climate change and human development.
