This award supports research in astrophysics connected to mergers of compact remnants of stellar deaths, black holes and neutron stars, which are strong sources of gravitational waves (GW), first directly detected in 2015 by NSF's Laser Interferometric Gravitational-Wave Observatory (LIGO). These cosmic mergers provide a unique laboratory for probing stellar astrophysics, cosmic expansion, and the nature of fundamental interactions of matter at extreme densities. The work addresses the priority areas of NSF's "Windows on the Universe" Big Idea. As LIGO's capabilities advance, the sample of detected mergers is in the hundreds, allowing us to characterize the GW source population and ultimately unravel the mysteries of how black holes and neutron stars come into mergers with each other. The rapidly growing observational samples present new computational challenges for GW astrophysics and bring to light new questions regarding their origins. Findings are disseminated to the astrophysics and AI communities as well as the broader public through open-source code bases, eye-catching visualizations, public lectures, hands-on workshops, and research-critical citizen science. Under this award, the team at Northwestern University will analyze LIGO data with a focus on addressing the computational challenges with AI methods and extracting new information from the data. A new statistical framework is developed and accelerated by state-of-the-art machine learning algorithms to analy