Location: Friedgen Family Seminar Room (SPH 2236)
Abstract: The nexus of big data science, AI, and machine learning for social epidemiology holds a promising avenue for advancing our understanding of disease distribution, social determinants, and health disparities within populations. This presentation delves into the applications, opportunities, and challenges of integrating big data science methods into social epidemiology.
Biography: Yulin Hswen, ScD MPH, is a Harvard-trained computational epidemiologist and assistant professor in the Department of Epidemiology and Biostatistics and the Bakar Computational Health Sciences Institute at UCSF, where she leads research on using artificial intelligence to uncover social patterns of disease and the transmission of information through social networks.
Participants: Feel free to bring lunch.