
Sasha Gavryushkina
School of Computer and Mathematical Sciences
Faculty of Sciences, Engineering and Technology
Eligible to supervise Masters and PhD (as Co-Supervisor) - email supervisor to discuss availability.
I am a Lecturer in Data Science and Statistics at the School of Computer and Mathematical Sciences at the University of Adelaide, where I develop methods for genomics data analysis with applications in macroevolution, epidemiology, and cancer research
My research focuses on developing statistical and computational methods for genomics data analysis, with applications in macroevolution, epidemiology, and cancer research.
Understanding the evolutionary relationships among tumour cells provides critical insights into how cancers develop, adapt, and spread. The advent and growing accessibility of single-cell sequencing technologies present an opportunity to reconstruct detailed cell lineage trees from tumour samples. My work focuses on testing and developing robust, accurate, and scalable methods to enhance our ability to interpret the complex evolutionary history of cancer at single-cell resolution.
Evolutionary histories reconstructed from genetic data provide a powerful tool for inferring population dynamics parameters across various application areas—for example, diversification rates in macroevolutionary studies, transmission rates in infectious disease epidemiology, and tumour growth rates in cancer research, among others. I am working on extensions and applications of birth–death models to improve such phylodynamic inference.
Classical statistical methods for inferring phylogenetic trees are well-established and reliable, but can be computationally intensive. My research focuses on developing likelihood-free inference techniques for phylogenetic analysis. My other research interests include machine learning techniques for sequencing data pre-processing, genotype–phenotype association studies, and other related problems.
-
Appointments
Date Position Institution name 2025 - ongoing Lecturer University of Adelaide 2024 - 2025 Senior Research Fellow Max Planck Institute of Geoanthropology 2021 - 2024 Research Fellow University of Canterbury 2018 - 2021 Postdoctoral Research Fellow University of Otago 2016 - 2018 Postdoctoral Research Fellow ETH Zurich -
Education
Date Institution name Country Title 2013 - 2017 University of Auckland New Zealand PhD -
Research Interests
-
Journals
Year Citation 2025 Truman, K., Vaughan, T. G., Gavryushkin, A., & Gavryushkina, A. S. (2025). The Fossilized Birth-Death Model Is Identifiable.. Syst Biol, 74(1), 112-123.
Scopus4 Europe PMC62025 Gavryushkina, A. S., Pinkney, H. R., Diermeier, S. D., & Gavryushkin, A. (2025). Filtering for Highly Variable Genes and High-Quality Spots Improves Phylogenetic Analysis of Cancer Spatial Transcriptomics Visium Data. JOURNAL OF COMPUTATIONAL BIOLOGY, 15 pages.
2020 Biggs, H., Parthasarathy, P., Gavryushkina, A., & Gardner, P. P. (2020). ncVarDB: A manually curated database for pathogenic non-coding variants and benign controls. Database, 2020, baaa105.
Scopus11 Europe PMC102019 Bouckaert, R., Vaughan, T. G., Barido-Sottani, J., Duchêne, S., Fourment, M., Gavryushkina, A., . . . Drummond, A. J. (2019). BEAST 2.5: An advanced software platform for Bayesian evolutionary analysis. Plos Computational Biology, 15(4), e1006650.
Scopus2824 Europe PMC17812018 Silvestro, D., Warnock, R. C. M., Gavryushkina, A., & Stadler, T. (2018). Closing the gap between palaeontological and neontological speciation and extinction rate estimates. Nature Communications, 9(1), 5237.
Scopus65 Europe PMC392018 Stadler, T., Gavryushkina, A., Warnock, R. C. M., Drummond, A. J., & Heath, T. A. (2018). The fossilized birth-death model for the analysis of stratigraphic range data under different speciation modes. Journal of Theoretical Biology, 447, 41-55.
Scopus74 Europe PMC502016 Ratmann, O., Van Sighem, A., Bezemer, D., Gavryushkina, A., Jurriaans, S., Wensing, A., . . . Fraser, C. (2016). Sources of HIV infection among men having sex with men and implications for prevention. Science Translational Medicine, 8(320), 320ra2.
Scopus101 Europe PMC862014 Gavryushkina, A., Welch, D., Stadler, T., & Drummond, A. J. (2014). Bayesian Inference of Sampled Ancestor Trees for Epidemiology and Fossil Calibration. Plos Computational Biology, 10(12), e1003919.
Scopus252 Europe PMC1952013 Gavryushkina, A., Welch, D., & Drummond, A. J. (2013). Recursive algorithms for phylogenetic tree counting. Algorithms for Molecular Biology, 8(1), 26.
Scopus9 -
Book Chapters
Year Citation 2021 Gavryushkina, A., & Zhang, C. (2021). Total-evidence dating and the fossilized birth-death model. In S. Y. W. Ho (Ed.), The Molecular Evolutionary Clock: Theory and Practice (pp. 175-193). Springer International Publishing.
DOI Scopus2 -
Conference Papers
Year Citation 2017 Gavryushkina, A., Heath, T. A., Ksepka, D. T., Stadler, T., Welch, D., & Drummond, A. J. (2017). Bayesian total-evidence dating reveals the recent crown radiation of penguins. In Systematic Biology Vol. 66 (pp. 57-73). England: Oxford University Press (OUP).
DOI Scopus218 Europe PMC160
Connect With Me
External Profiles