1. Utilizing Swift-XRT Data to Identify Source Classes in Fermi Unassociated Objects Open Access Author: Pryal, Matthew Title: Utilizing Swift-XRT Data to Identify Source Classes in Fermi Unassociated Objects Area of Honors: Astronomy and Astrophysics Keywords: FermiSwiftX-raysGamma-raysData MiningMachine LearningAstrostatistics File: Download matthew_pryal_honors_thesis.pdf Thesis Supervisors: Abraham David Falcone, Thesis SupervisorAlexander Wolszczan, Thesis Honors Advisor
2. Detecting Type II-P Supernova Precursor Emission via Machine Learning Open Access Author: Tartaglia, Anna Title: Detecting Type II-P Supernova Precursor Emission via Machine Learning Area of Honors: Astronomy and Astrophysics Keywords: Transient AstronomySupernovaeMachine Learning File: Download anna_tartaglia_thesis.pdf Thesis Supervisors: Donald P Schneider, Thesis SupervisorCindy Yuexing Gulis, Thesis Honors Advisor
