Regular biography
Rachel Wang is an Associate Professor in the School of Mathematics and Statistics at The University of Sydney. Her research areas include Networks and complex systems, Statistical theory, Computational statistics and machine learning, Bioinformatics, and Bayesian statistics. She teaches courses such as STAT4028, offering lectures and tutorials during Semester 1, 2026. Her profile page provides details about her academic and professional activities within the university.
Scholar-generated biography
Y. X. Rachel Wang is a researcher in statistical network modelling, statistical machine learning, and computational biology. Her work focuses on developing statistical methods for gene network reconstruction, gene–gene interactions, and brain network analysis. She has contributed to the integration of single-cell RNA-seq and ATAC-seq data using transfer learning, as well as the analysis of chromosome conformation capture experiments. Her research also includes population genetics, gene coexpression measures, and network modelling of topological domains using Hi-C data. Wang's publications highlight her expertise in likelihood-based model selection, sparse canonical correlation analysis, and variational inference for community detection.