About Dr. Ebele Mogo
Dr. Ebele Mogo is a public health scientist working at the intersection of population health and computational methods. Her work focuses on how clinical and behavioral risks compound across populations, and how large-scale data and computational approaches can identify those at highest risk and determine which preventive interventions improve outcomes in real-world health systems with a particular focus on underserved populations.
Currently she serves as Principal Investigator on a federally funded research project applying computational methods to large-scale standardized clinical data across community health centers, identifying high-risk population subgroups and estimating intervention effects to guide more precise prevention strategies, with a focus on cardiometabolic disease in underserved populations.
Her scientific background spans behavioral health, evidence synthesis, and digital health across academic, startup, and global health contexts — including work with WHO, UNICEF, the Gates Foundation, Cambridge and McGill universities. She serves on the Board of the Campbell Collaboration and was on the inaugural steering group of Cambridge's Centre for Human-Inspired Artificial Intelligence.