Rate My Professor Kim-Anh Le Cao

Professor Kim-Anh Le Cao is Professor in Statistical Genomics in the School of Mathematics and Statistics, Faculty of Science, at the University of Melbourne, where she also serves as Director of Melbourne Integrative Genomics and Director of Research. She earned her PhD in Applied Statistics from the Université de Toulouse in 2009, for which she received the Laurent-Duhamel triennial prize from the French Statistical Society. Following postdoctoral positions at the University of Queensland's Institute for Molecular Bioscience and Diamantina Institute from 2008 to 2017, she joined the University of Melbourne as an NHMRC Career Development Fellow and group leader. She secured consecutive NHMRC Career Development Fellowships: CDF1 from 2015 to 2019 valued at $419,000 for developing statistical methodologies in clinical cancer studies, and CDF2 from 2019 to 2022 valued at $483,000 for microbiome biomarker discovery.

Le Cao's research centers on computational statistics and biology, developing novel multivariate projection-based methods for integrating high-dimensional omics data including transcriptomics, proteomics, metabolomics, microbiome, and single-cell multi-omics. Her lab has created the mixOmics R package, featuring 19 methodologies for omics feature selection and data integration, ranking in the top 5% of Bioconductor downloads with around 80,000 annually. Key tools include DIABLO for multi-omics on the same samples, MINT for independent studies, mixMC for microbial communities, timeOmics for time-course data, LUPINE for microbial networks, and Φ-Space for single-cell phenotyping. She co-authored the book Multivariate Data Integration Using R: Methods and Applications with the mixOmics package (CRC Press, 2021). Highly cited publications encompass mixOmics: An R package for ‘omics feature selection and multiple data integration (Rohart et al., PLOS Computational Biology, 2017), DIABLO: an integrative approach for identifying key molecular drivers from multi-omics assays (Singh et al., Bioinformatics, 2019), and Sparse PLS discriminant analysis: biologically relevant feature selection and graphical displays for multiclass problems (Lê Cao et al., Biostatistics, 2011). Her awards include the Moran Medal from the Australian Academy of Science (2019), Georgina Sweet Award for Women in Quantitative Biomedical Science (2019), University of Melbourne Dean’s Award for Excellence in Research (mid-career, 2019), and Superstars of STEM (Science & Technology Australia, 2020–2022). Le Cao supervises PhD students on topics like microbiome analysis and single-cell multi-omics integration, teaches statistical genomics, and leads workshops on mixOmics.