Explore the application of UniverseMachine to model dwarf galaxy formation in this 26-minute conference talk by Richie Wang from Stanford University. Delve into the vast potential of astrostatistics and machine learning tools in galaxy formation and evolution studies. Gain insights into abundance matching techniques, multiresolution cosmological simulations, and the challenges of modeling high-mass galaxies. Examine the believability of the results, discuss ongoing work on degeneracy and unpublished data, and consider future directions for model constraints. Learn about disk re-simulations, Milky Way simulations, and the Symphony project. Conclude with a summary and engage in a Q&A session to further understand the implications of this research in the field of astrophysics.