Xuewen’s research interest lies in causal inference methods, bayesian inference, and their applications in population health. Xuewen’s worked on chain event graphs during her PhD and developed a hierarchical model to improve predictions of machine’s failure by incorporating the bespoke causal algebras. Before joining LSE, Xuewen worked on continuous-time g-methods to assess the effect of time-varying treatment when the treatment decision changes sporadically throughout the follow-up period. Her current work focuses on quasi-experimental design and policy evaluation.