I am a multidisciplinary Spatial Scientist and Remote Sensing Analyst specialising in the processing and analysis of large-scale spatial and temporal environmental datasets. My work bridges advanced geospatial engineering and environmental monitoring, utilising drone and satellite imagery alongside high-performance computing (HPC) infrastructure to extract actionable intelligence across vast geographic scales.

Most recently, I served as the Environmental Scientist (Spatial) in the Water and Wetlands team in the Department of Climate Change, Energy, the Environment and Water (DCCEEW). I use drone, aerial, and satellite imagery to monitor wetland inundation and assess the ecological outcomes of environmental flows across the NSW portion of the Murray–Darling Basin. My work focused on developing new spatial methods to better understand wetland regimes in complex environments, and collaborating closely with vegetation, waterbird, and frog monitoring programs to support evidence‑based environmental management.

I previously worked as the Seabird Remote Sensing Ecologist with the British Antarctic Survey’s Wildlife from Space team. In this role, I used very high-resolution satellite imagery to monitor seabird populations on some of the most remote islands on Earth—places where traditional research methods are often not feasible. My career has taken me to many remote and exciting locations, including isolated islands and the stunning landscapes of Antarctica.

I have a background in functional ecology and evolutionary biology, and my broader research interests focus on understanding how animals adapt to changing environments. I use large-scale datasets to answer novel, wide-scale ecological questions.

Research Interests

  • Quantifying wetland inundation dynamics using drone, satellite, aerial and ground surveys by developing automated spatial workflows for large-scale spatial processing and analysis.
  • Extracting long-term environmental trends and regime shifts from expensive historical datasets and high-frequency sensor networks.
  • Monitoring remote seabird populations and inaccessible ecosystems using very-high resolution satellite and drone imagery.
  • Engaging citizen science and crowdsourced data to build annotation frameworks and machine-learning training datasets for wildlife monitoring and identifying suitable habitats.
  • Conducting large-scale macroecological studies with expansive datasets, including functional traits and evolutionary adaptation investigations.