I am a Research Associate at MRC Biostatistics Unit working with Robert Goudie. Before starting my research at University of Cambridge, I completed my master in Applied Statistics at University of Oxford, and finished my PhD in the Oxford-Warwick Statistics Programme at University of Warwick. 

My research interests include graphical models, Bayesian inference and causal inference. My PhD project developed causal algebras on Chain Event Graphs and proposed a framework for a hierarchical causal analysis. I worked closely with reliability data with free texts, so I am also interested in Natural Language Processing and combining it with causal analysis. Please check my personal website for more details about me.   

Publications

• Yu, X. and Smith, J.Q. 2022, Identifying causal effects on chain event graphs for remedial interventions. Under review. 
• Yu, X. and Smith, J.Q., 2021. Causal algebras on chain event graphs with informed missingness for system failure. Entropy, 23(10), p.1308.  
• Strong, P., Shenvi, A., Yu, X., Papamichail, K.N., Wynn, H.P. and Smith, J.Q., 2021. Building a Bayesian decision support system for evaluating COVID-19 countermeasure strategies. Journal of the Operational Research Society, pp.1-13. 
• Yu, X. and Smith, J.Q., 2021. Hierarchical Causal Analysis of Natural Languages on a Chain Event Graph. arXiv preprint arXiv:2110.01129. 
• Yu, X., Smith, J. Q. and Nichols, L., 2020. Bayesian Learning of Causal Relationships for System Reliability. Proceedings of the International Symposium on Reliability Engineering and Risk Management (ISRERM 2020).