My PhD research applies statistical machine learning to problems in record linkage, including active labelling of ground truth and propagation of linkage uncertainty. More broadly, I am interested in human-in-the-loop machine learning systems, probabilistic graphical models, sampling and approximate inference. I’m a strong believer in the benefits of reproducible research, and strive to release open source code where possible.
|Sep 17, 2020||Our paper on distributed Bayesian entity resolution was accepted for publication in the Journal of Computational and Graphical Statistics.|
|Jul 22, 2020||I presented my PhD research in a completion seminar—one of the final milestones of my candidature.|
|Aug 13, 2019||I’m presenting our work on distributed Bayesian entity resolution at the Conference on Current Trends in Survey Statistics at the National University of Singapore.|