Machine Learning & Epidemiology with Elaine Nsosie

Today we continue our ICML series with Elaine Nsoesie, assistant professor at Boston University. Elaine presented a keynote talk at the ML for Global Health workshop at ICML 2020, where she shared her research centered around data-driven epidemiology. In our conversation, we discuss the different ways that machine learning applications can be used to address global health issues, including use cases like infectious disease surveillance via hospital parking lot capacity, and tracking search data for changes in health behavior in African countries. We also discuss COVID-19 epidemiology, focusing on the importance of recognizing how the disease is affecting people of different races, ethnicities, and economic backgrounds.