Dr Wanchuang Zhu (University of Sydney)
Bachelor of Science (Statistics)
PhD (Mathematics & Statistics)
Dr Zhu completed a PhD at the School of Mathematics and Statistics, University of New South of Wales in 2017. He is currently a postdoctoral research fellow at the Centre for Translational Data Science (CTDS). His work at CTDS includes developing new statistical approaches to explore the questions in social science, for example, the casual relationship between children’s obesity with other covariates, such as their families’ social-economic status.
Wanchuang’s expertise includes computational statistics on Markov Random Field and rank aggregation. He has developed several statistical algorithms to tackle the normalising constant issue in the Potts model (a discrete version of Markov Random Field). The benefits of his algorithms include high statistical accuracy, high computational efficiency and high flexibility.
Rank aggregation aims to achieve a consensus ranking list from multiple ranking lists. Wanchuang has developed several statistical models on rank aggregation. These models can derive the aggregated ranking list and evaluate the reliability of the rankers simultaneously. Thus, these models filled the gap in the literature of rank aggregation.
He has published several peer-reviewed papers in prestigious journals, such as Journal of Computational and Graphical Statistics (JCGS). His active research areas also include Approximate Bayesian Computation and Sequential Monte Carlo.