Scott Hosking leads a team of scientists and engineers across both the British Antarctic Survey and The Alan Turing Institute who are focused on the development of AI and digital twin technologies for understanding, monitoring and predicting environmental change.
His projects include the intelligent fusion of data from satellite and in-situ surface sensors to help understand our changing planet; probabilistic machine learning for localised climate impacts; AI for seasonal sea ice forecasting and improving climate models; and computer vision toolkits for tracking environmental change and wildlife monitoring.
Scott is also a Co-Director for the Centre for Doctoral Training (CDT) in the Application of AI to the study of Environmental Risks (AI4ER), a £6m UKRI funded programme to train over 50 top students to become future global leaders in environmental science.
- Digital Twinning for the natural environment
- Application of AI for climate risks, and the prediction of high-impact weather events
- Intelligent post-processing of climate data, including bias correction and downscaling
- Simplifying data analysis pipelines for the application of AI, including Pangeo.io (a cloud platform for Big Data geoscience)
- Probabilistic machine learning, providing robust uncertainty estimates for business and environmental policy decision making
- Combining Little Data and Big Data
- Scalable data science methods for large N-dimensional spatiotemporal datasets
- Flexible approaches for irregularly sampled and fragmented datasets