Jacob Jameson is a student in the Harvard PhD Program in Health Policy, in the Decision Sciences track. Jameson is an educational innovation scholar at CHDS and a collaborator on multimedia innovation with the Global Health Education and Learning Incubator, currently working with Dr. Sue Goldie to develop learning modules on queuing theory and how it could be used to optimize important systems in healthcare.

Jameson has a longstanding interest in teaching, pedagogy, and education. He has served as a teaching fellow for multiple courses, teaches the Public Policy/Health Policy PhD Math Camp, and taught a short course at the 2023 Society for Medical Decision Making (SMDM) North American Meeting. Prior to starting the PhD program, Jameson was a middle school mathematics teacher in New Haven, CT.

Jameson is a Predoctoral Trainee in the T32 training program in Comparative Effectiveness Research for Suicide Prevention, funded by the U.S. National Institute of Mental Health. Jacob’s research focuses on machine learning and computational approaches to optimization and dynamic treatments in health decision-making.