Supermassive black holes live in the centers of most galaxies, including our own Milky Way galaxy. Millions to billions of times more massive than the Sun, supermassive black holes provide crucial insight for understanding how galaxies formed and evolved. When two galaxies collide, their supermassive black holes can form a binary system that spirals together and merges. This cosmic dance creates extremely powerful “gravitational waves” (GWs), which are ripples in the fabric of spacetime. This project will use computer models to study how binary supermassive black holes evolve and to improve GW predictions. The project will also expand the Gator Artificial Intelligence (AI) Camp for high school students, which was created by the lead investigator and launched in Summer 2024. This program will create research and educational opportunities to undergraduate students. The research team will design an improved framework for binary SMBH population modeling for PTAs and the upcoming Laser Interferometer Space Antenna (LISA) mission. This work will address the following fundamental research questions: (1) Which observables and theoretical assumptions dominate the uncertainty in the SMBH population characteristics inferred from the gravitational wave background and future LISA events? (2) How efficiently do SMBH binaries inspiral and merge in different environments, and what is the best way to model this process for PTA and LISA data analysis? To address these questions, the team wi