Xiaoyi Zhang

Xiaoyi Zhang’s research interest centers on how innovations in artificial intelligence can be translated into tangible improvements in healthcare systems. Her work encompasses explainable machine learning to guide clinical decision-making, temporal deep learning for chronic disease monitoring in complex patient profiles, and pioneering the use of large language models (LLM) to augment existing healthcare quality measures. Her research builds upon extensive experience developing large data infrastructure and analytical pipelines, including national-scale data from the Veterans Health Administration (VA) and enterprise data warehouses across multiple health systems. Xiaoyi is advised by Professor Gang Luo at UW and Professor Steven Zeliadt at VA. Previously, Xiaoyi received a BS in Applied Mathematics and a BA in Chemistry from Emory University, and an MS in Data Science from New York University.