Stephanie's research focuses on applied statistics, in particular improving the application of machine learning techniques in the field of hydrology and water resources. Stephanie's career started as a water resources engineer, followed by an MSc in applied mathematics and a PhD in statistics, with the aim of improving the extraction and visualisation of meaningful information from the vast amount of water-related data that is currently collected.
Supervised and unsupervised learning techniques
PhD - Statistics, UNSW, Australia
MSc - Applied and Computational Mathematics, Oxford University, UK
Clark, S., Sarlin P., Sharma A., & Sisson S.
(2015). Increasing dependence on foreign water resources? An assessment of trends in global virtual water flows using a self-organizing time map. Ecological Informatics. 26, 192-202. doi: 10.1016/j.ecoinf.2014.05.012