Danielle Norman
Curriculum Vitae
- 2018–Present: PhD Researcher, QMEE CDT, Institute of Zoology and Imperial College London
- 2017–2018: MSc in Mathematical Biology, Ecology and Medicine, Heriot-Watt University
- 2013–2014: Shelf Seas Modeller - undergraduate placement, National Oceanography Centre
- 2011–2015: BSc in Mathematics, University of Bath
Research Interests
With a background in mathematical biology, I am interested in applying quantitative methods and tools to ecological problems and to inform conservation practices. Previous research has included modelling the transmission of West Nile Virus to roosting robins, and investigating suitable stronghold forest composition to support viable populations of red squirrels in Scotland.
Current Research
Changes in land use and climate affect the distribution, abundance and behaviour of species globally. Management and mitigation of these processes requires a good understanding of how they affect wildlife, which requires effective monitoring over large areas and long time periods. Mammals are often scarce, shy, elusive or nocturnal, so are difficult to monitor. Camera trapping has revolutionised prospects for monitoring mammals but generates huge numbers of images to be analysed. My PhD project aims to mobilise machine learning techniques to push forward our ability to automatically process large quantities of camera trap imagery, with a particular focus on using the data generated to understand the dynamics of interactions between species and their environment.
My funding is provided by the CDT in Quantitative and Modelling Skills in Ecology and Evolution (QMEE).
Supervisors
Marcus Rowcliffe, Institute of Zoology
Rob Ewers, Imperial College London
Robin Freeman, Institute of Zoology