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Explore the fascinating world of dark matter detection through stellar observations in this 30-minute conference talk by Lina Necib from MIT. Delve into cutting-edge research that applies astrostatistics and machine learning techniques to galaxy formation and evolution. Discover how Integral Field Unit surveys, galaxy morphology studies, and advanced data analysis methods are revolutionizing our understanding of the universe. Learn about the potential of outlier detection algorithms in identifying anomalous galaxies and how these tools can bridge the gap between observations and theoretical models. Gain insights into the future of astrophysics with upcoming projects like Rubin, DESI, Roman, Euclid, and the SKA. This talk, part of a conference organized by the Kavli Institute for Theoretical Physics, emphasizes the translation of data-driven results into physical understanding, offering a unique perspective on the application of data science to unravel the mysteries of galaxy formation and evolution.
