Dr. Xin Zhou is an Associate Professor in the Department of Biostatistics at the Yale School of Public Health. She earned her Ph.D. in Biostatistics from the University of North Carolina at Chapel Hill and completed a postdoctoral fellowship at the Harvard T.H. Chan School of Public Health. Her research lies at the intersection of artificial intelligence, statistical methodology, and public health applications, with a focus on improving healthcare outcomes through data-driven decision-making. Dr. Zhou’s work leverages machine learning, causal inference, and high-dimensional data analysis to address complex challenges in personalized medicine and population health. She has developed novel AI-integrated statistical methods to better model measurement errors, correct biases in observational studies, and enhance the design and analysis of clustered randomized trials. One of her key interests is applying AI to tailor precision health interventions, ensuring that preventive strategies and treatments are not only effective but also equitable. She is actively involved in projects that use predictive modeling and risk stratification algorithms to identify at-risk populations and inform policy-level decisions in public health. In addition to her research, Dr. Zhou is a dedicated educator and mentor, guiding students and researchers in both the theoretical and practical applications of AI and biostatistics in medicine and public health.