Sasha Gavryushkina

Sasha Gavryushkina

School of Computer and Mathematical Sciences

Faculty of Sciences, Engineering and Technology

Dr Sasha Gavryushkina is a Lecturer in Data Science and Statistics at the School of Computer and Mathematical Sciences at the University of Adelaide. Her research focuses on developing statistical and computational methods for genomics data analysis. In particular, Sasha is working on methods for reconstructing tumor evolution using single-cell RNA sequencing and multi-omics data. She also explores the application and extension of birth-death models in macroevolution and epidemiology to estimate diversification and epidemiological parameters. The methods she has developed have been implemented as software packages for BEAST2, a widely used tool for phylogenetic tree reconstruction. Additionally, Sasha is interested in applying machine learning techniques for pre-processing of sequencing data analysis, genotype-phenotype association studies, and other 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

  • 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.
    DOI Scopus3 Europe PMC6
    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.
    DOI Scopus11 Europe PMC10
    2019 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.
    DOI Scopus2689 Europe PMC1625
    2018 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.
    DOI Scopus62 Europe PMC35
    2018 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.
    DOI Scopus70 Europe PMC46
    2016 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.
    DOI Scopus99 Europe PMC85
    2014 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.
    DOI Scopus242 Europe PMC183
    2013 Gavryushkina, A., Welch, D., & Drummond, A. J. (2013). Recursive algorithms for phylogenetic tree counting. Algorithms for Molecular Biology, 8(1), 26.
    DOI 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 Scopus209 Europe PMC147
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