Marcus Russi is a Research Assistant, primarily working on the development of an agent-based model of tuberculosis within an HIV-endemic environment. He is passionate about the application of techniques from the world of computer science to problems in epidemiologic modeling. Recently, his work has centered on approaches to highly parallel application design for agent-based model calibration and execution, with the goal of more accurately capturing individual-level phenomena in TB-HIV coepidemics. He completed his undergraduate studies in Computer Science at Yale University in 2018, and has worked for the lab since graduation.
|BS||Yale University, Computer Science|