Some of the least understood patterns in brightness variability are those that come from accreting compact objects, such as active galactic nuclei (AGN) and X-ray binary sources (XRB). The Vera C. Rubin Observatory will provide an unprecedented number of objects in its Legacy Survey of Space and Time (LSST). A researcher and her team at Villanova University, has been awarded a Mathematical and Physical Sciences Ascending Faculty Catalyst (AFC) Award to investigate novel ways to identify accreting compact objects from within the vast LSST dataset. Studying large numbers of these objects will help improve our understanding of how these compact objects interact with their environment. This Award will also enable the development of a regional network of scientists, teachers, and students from a range of institutions that use the Rubin Observatory to perform research in astronomy. A critical pillar of achieving regional awareness in leveraging Rubin data will be a 2-day workshop hosted at Villanova University that provides training on accessing Rubin data and support for designing projects that leverage the capabilities of Rubin. Over the course of the AFC award, the proposer will use simulated data previews from LSST as well as archival observations from TESS to curate a sample of synthetic light curves of AGN and XRBs that can be used to test novel time series methodologies. A novel technique from nonlinear dynamics, Recurrence Plots, combined with machine learning techniqu