Fundamental questions in nuclear physics are deeply connected to neutron star observations. In this talk, Andrew W. Steiner of UT Physics will explain how scientists are answering these questions using a combination of data from nuclear experiments and neutron star observations, theoretical models of hot and dense matter, and numerical simulations. Answering these questions demands a level of effort beyond that of a single research group, so Steiner explains how progress is being made through collaborations like the Nuclear Physics for Multi-Messenger Mergers Focused Research Hub. He will summarize recent results on both the speed of sound and the composition of dense matter and show how scientists are enhancing astrophysical simulations by improving the nuclear physics input. Finally, he will show how machine learning is accelerating progress.