Ying Cui

I am a postdoctoral fellow in Biomedical Data Science at Stanford University. My research advances the statistical foundations of biomedical data science. I develop interpretable and reproducible methods that combine nonparametric and semiparametric modeling, machine learning, and causal inference to address practical questions in precision health and trustworthy AI.

My collaborations span clinical trials, medical devices, electronic health records, drug discovery, and responsible clinical AI. Current projects in drug discovery and development focus on reinforcement learning and ensemble learning for dynamic, data-driven decision-making, conformal inference for uncertainty quantification, and generative AI for validation and benchmarking. Other projects include nonparametric and semiparametric methods for assessing dynamic covariate effects, personalized clinical indices derived from large-scale EHR data, and evaluation of treatment efficacy across prioritized outcomes.

I received my Ph.D. in Biostatistics from Emory University. I previously earned a B.S. in Statistics from Nankai University and completed a statistics internship at Pfizer.