Josh is interested in using machine learning to inform policy aimed at reducing health inequalities. As a data scientist in both clinical and public health settings, he has worked on projects including analyzing electronic medical records to measure the socioeconomic disparities in cancer screening and processing news articles to identify epidemics around the world. As a Keenan Research Summer Student at the Mishra Lab (2016), he examined the relationship between syphilis re-infection and epidemic control. He is currently pursuing a Master of Data Science at Harvard University, where is further studying the connections between data analysis and the social determinants of health, while wrestling with the ethical and legal challenges of using algorithms to create public policy. He holds a B.Sc. in Mathematics from Dalhousie University with a minor in Contemporary Studies. For this project, Josh was awarded the best student poster award at the 2017 Association for Medical Microbiology and Infectious Diseases (AMMI) national conference. Josh’s project with the lab includes the following publication:
- Feldman J, Mishra S. (2019). What can the proportion of re-infections tell us about the basic reproductive number in syphilis epidemics: A modeling study. Infect Dis Model, 4, 257-264.