Xuewen Yu

Xuewen Yu is a Research Fellow at the Department of Statistics, London School of Economics and Political Science (LSE). Her expertise spans causal inference, graphical models, Bayesian inference, and their applications in population health and reliability engineering. Previously, she developed hierarchical models for system failure prediction using causal algebras and worked on continuous-time g-methods for time-varying treatments. Her current research focuses on quasi-experimental design and policy evaluation.

Key research interests include causal chain event graphs, Bayesian decision support systems for public health crises like the COVID-19 pandemic, and integrating causal methods into engineering and policy analysis. Her work bridges theoretical statistical frameworks with practical applications in healthcare, infrastructure maintenance, and poverty-driven policy assessment.

Recent publications highlight contributions to causal analysis in reliability engineering, Bayesian modeling of pandemic countermeasures, and the development of decision support tools for resource adequacy and policy evaluation. Her interdisciplinary approach combines statistical rigor with real-world problem-solving.