Donglin Zeng, PhD, is a Professor of Biostatistics at the University of Michigan School of Public Health. His research spans precision medicine, dynamic treatment regimes, machine learning, high-dimensional inference, semiparametric modeling, and survival analysis, with applications in clinical trials and electronic health records. He develops statistical tools to support diagnostics, prediction, and treatment decisions across conditions including cancer, infectious disease, obesity, cardiovascular disease, and psychiatric disorders. In MAPCI, he contributes methodological depth in biostatistics and data science for personalization.