Disease Nowcasting Using Integrated and Adaptive Statistical Models

Yang Xiao is a Ph.D. candidate in Statistics at King Abdullah University of Science and Technology (KAUST). With a background that bridges rigorous mathematical theory and industrial application, his work focuses on improving the accuracy of real-time predictive modeling in high-stakes environments.

Before joining KAUST, Yang spent several years as a Statistician in the pharmaceutical industry, where he specialized in experimental design, protocol development, and ensuring 100% numerical reproducibility for core research frameworks under strict regulatory standards. His academic journey began with a dual-degree background in Applied Statistics and Actuarial Science, followed by an MSc in Statistics with Data Science from the University of Edinburgh, where he focused on multi-modal signal extraction and latent pattern recognition in epidemiological data.