Varvara Vetrova

Senior LecturerVarvara Vetrova

Postgraduate Mentor
Jack Erskine 712
Internal Phone: 92473

Research Interests

Applied statistics and machine learning in environmental domain. Applications of deep neural networks for fine-grained recognition.

Recent Publications

  • Bardsley E. and Vetrova V. (2019) Estimating evaporation for low wind speeds at an eddy correlation site: Potential for windbreak evaluation. Journal of Hydrology New Zealand 58(1): 57-63.
  • Bardsley E., Vetrova V. and Dao NH. (2019) Line mesh distributions: an alternative approach for multivariate environmental extremes. Stochastic Environmental Research and Risk Assessment 33(2): 633-643. http://dx.doi.org/10.1007/s00477-018-1642-x.
  • Mason NWH., Palmer DJ., Vetrova V., Brabyn L., Paul T., Willemse P. and Peltzer DA. (2017) Accentuating the positive while eliminating the negative of alien tree invasions: a multiple ecosystem services approach to prioritising control efforts. Biological Invasions 19(4): 1181-1195. http://dx.doi.org/10.1007/s10530-016-1307-y.
  • Vetrova V. and Bardsley E. (2017) A simple nonparametric index of bivariate association for environmental data exploration. Environmental Modelling and Software 96: 283-290. http://dx.doi.org/10.1016/j.envsoft.2017.07.006.
  • Vetrova V. and Bardsley WE. (2017) R Code for Data Simulation with Moment Matching. Open Water 4(1) 7: 72-74.