My research focuses on developing scalable computer vision and deep learning methods to identify and track individual animals in wild marine environments, using distinctive signatures in video, audio, and movement patterns. My aim is to better understand animal behaviour, from how fish navigate coral reefs to how seabirds coordinate nest visits during breeding, while developing automated, non-invasive tools for marine biodiversity monitoring and conservation.
I am supervised by Cait Newport (Animal Perception and Cognition Group), Andrew Zisserman (VGG), Tim Guilford (OxNav), and Xiaowen Dong (Machine Learning Research Group).
I am also a data scientist at the World Data Lab, working on pipelines measuring and forecasting the world's progress towards the UN Sustainable Development Goals, mainly relating to greenhouse gas emissions, biodiversity, water and development.
I hold a BSc in political science from UCL and a MSc in data science from Oxford. Outside of work, I lead social impact work as a Global Shaper in the London iii Hub, and in my free time enjoy birdwatching, art, reading (mostly romantasy as of late), cooking and baking, and swimming.
