Explore the importance of outliers in galaxy formation and evolution through this 30-minute conference talk by Dovi Poznanski from Tel Aviv University. Discover how astrostatistics and machine learning tools are revolutionizing the field, particularly in the analysis of Integral Field Unit surveys and galaxy morphology data. Learn about outlier detection algorithms that identify anomalous galaxies challenging current paradigms, and how these discoveries will accelerate with upcoming astronomical surveys. Gain insights into the application of data science tools for linking observations with theoretical models, including cosmological simulations and semi-analytic models. Understand the conference's goal of translating data-driven results into physical understanding, emphasizing the potential of these tools to advance our knowledge of galaxy formation physics.