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AI for the study of Environmental Risks (AI4ER)

UKRI Centre for Doctoral Training


Student Department Topic area PhD project title
Matt Allen Dept of Geography Ecology, remote sensing Automated tree species classification from forest terrestrial laser scanning data
Hamish Campbell Dept of Plant Sciences Peatland restoration,  carbon credits An accurate, scalable and low-cost method for assessing peatland regeneration projects using artificial intelligence methods
Katie Green British Antarctic Survey and Dept of Computer Science and Technology Marine ecosystems Understanding ecosystem dynamics to protect marine ecosystems
Madeline Lisaius Dept of Computer Science and Technology Machine learning for remote sensing Self-supervised learning approaches in earth observation leveraging physical knowledge about the Interaction of electro-magnetic radiation with vegetation canopies as applied to agriculture (Partner Mantle Labs).
Joycelyn Longdon Dept of Computer Science and Technology, Deforestation and forest management Monitoring Ghanaian forests with bioacoustics, machine learning and indigenous knowledge. – Partner BTO
Simon Mathis Dept of Computer Science and Technology Ecosystems Understanding the cold adaptation of life at the protein and cellular level
Jonathan Roberts Dept of Engineering Environmental land-cover classification Computer vision, ‘few-shot’ learning, remote sensing, large-scale, multimodal model, land cover, unsupervised
domain adaptation.
Sofija Stefanovič Dept of Computer Science and Technology Mining, pollution, water access, soil health Monitoring impacts of exploratory mining with community citizen science and AI systems