Stephen Leslie

Professor Stephen Leslie is Professor of Statistical Genomics in the School of Mathematics and Statistics, Faculty of Science, at the University of Melbourne. A statistician working in mathematical genetics, he develops advanced statistical methods to analyze genomic data, elucidating fine-scale population genetic structure, ancestry inference, HLA and KIR imputation, genetic variation in autoimmune diseases, and novel variation in Indigenous Australian genomes. His research integrates statistics with genomics to address key questions in population genetics and systems biology.

Leslie earned his doctorate from the Department of Statistics at the University of Oxford. He completed postdoctoral positions at the University of Cambridge and the Wellcome Trust Sanger Institute, followed by a Research Fellowship at the University of Oxford. Since joining the University of Melbourne in 2016 as Associate Professor, he was promoted to Professor in 2019. He has been recognized with the 2016 Woodward Medal, the University of Melbourne's highest award for early-career research excellence, and the 2019 Moran Medal from the Australian Academy of Science for major contributions to mathematical genetics. Leslie is involved in projects including Immune-Associated Genetic Variation and Autoimmune Disease, Characterising the Mutagenic Effects of Neuroinflammation in Primary Progressive MS, and An Indigenous Australian Reference Genome for Indigenous Inclusion in Genomic Medicine. He contributes to Melbourne Integrative Genomics.

Key publications include 'The fine-scale genetic structure of the British population' (Nature, 2015), mapping genetic ancestry across Britain; 'Indigenous Australian genomes show deep structure and rich novel variation' (Nature, 2023); 'Imputation of KIR types from SNP variation data' (American Journal of Human Genetics, 2015); 'High-density mapping of the MHC identifies a shared role for HLA-DRB1*01:03 in inflammatory bowel diseases' (Nature Genetics, 2015); and 'Genome-wide association study of eosinophilic granulomatosis with polyangiitis reveals genomic loci stratified by ANCA status' (2020). His work has profoundly influenced statistical genomics, enabling precise genetic analyses for disease studies and population history reconstruction.

Professional Email: stephen.leslie@unimelb.edu.au