Summary
I am currently a Research Associate in Statistics in the Department of Mathematics, Imperial College London. My principal research focus has been on developing theory, methodology and computational tools to solve emerging problems in biomedicine and science more generally, especially under fully Bayesian settings. Specific areas of interest include biostatistics, mixture models, hidden Markov models, causal inference.
Publications
Journals
Luo Y, Graham DJ, McCoy EJ, 2023, Semiparametric Bayesian doubly robust causal estimation, Journal of Statistical Planning and Inference, Vol:225, ISSN:0378-3758, Pages:171-187
Luo Y, Stephens D, Buckeridge DL, 2021, Bayesian clustering for continuous-time hidden Markov models, Canadian Journal of Statistics-revue Canadienne De Statistique, ISSN:0319-5724
Luo Y, Stephens DA, 2021, Bayesian inference for continuous-time hidden Markov models with an unknown number of states, Statistics and Computing, Vol:31, ISSN:0960-3174, Pages:1-15
Luo Y, Stephens DA, Verma A, et al., 2020, Bayesian latent multi-state modeling for nonequidistant longitudinal electronic health records, Biometrics, Vol:77, ISSN:0006-341X, Pages:78-90
Powell GA, Verma A, Luo Y, et al., 2019, Modeling Chronic Obstructive Pulmonary Disease Progression Using Continuous-Time Hidden Markov Models., Stud Health Technol Inform, Vol:264, ISSN:0926-9630, Pages:920-924