Dr Clara Grazian
Double PhD (Applied Mathematics & Statistics)
Clara Grazian received a joint PhD in 2016 from University Paris-Dauphine (France) and Sapienza University of Rome (Italy), working on Bayesian analysis for mixture models and copula models. She then joined the Nuffield Department of Medicine and the Big Data Institute of the University of Oxford to work on an international project trying to investigate mechanisms of drug resistance developed by tuberculosis. Before joining the School of Mathematics and Statistics of the University of Sydney, Clara was Senior Lecturer in Statistics at University of New South Wales.
Clara Grazian’s research focuses on Bayesian modelling and computational aspects. In particular, she is interested in Bayesian clustering through mixture models, and the study of properties of prior distributions for clustering problems, and in dependence models such as copula models, when the interest lies on functional of the dependence. Part of her research is focused on computational algorithms to efficiently estimate Bayesian models, such as MCMC, ABC and variational Bayes. She has developed extensive applied collaborations, including modelling animal behaviours, association studies in genomics, portfolio optimization models in finance, long memory processes, machine learning for cybersecurity, modelling air pollution and its effect on vegetation and human health, modelling preferences.