Yein Jeon

Yein Jeon’s research interest is the application of deep learning to multi-modal health data. Previously, she earned her B.S. in Statistics and M.S. in Data Science from George Washington University. Following her experience in the industry, she pursued an M.S. in Biostatistics at Georgetown University to transition into the field of public health. During her time at Georgetown University, she worked in the lab, focusing on analysis for metabolite biomarker selection and cancer classification utilizing deep learning. Outside the lab, she performed quantitative bias analysis of the confounding effects between NOAC and GI bleeding compared to Warfarin. After completing M.S. in Biostatistics, she joined Johns Hopkins University, participating in epidemiology research related to diabetes and cardiovascular disease using data from wearable devices, surveys, and EHR. Currently, she is pursuing a Ph.D. in Biomedical and Health Informatics at the University of Washington.