Artificial Intelligence Lab

The BAS Artificial Intelligence Lab (or ‘BAS AI Lab‘) aims to foster the application of various machine learning (and adjacent) techniques to the rapidly growing, complex, and heterogeneous body of environmental data.

AI methods are now routinely used across many areas of BAS Science, including: oceanography; climate science; glacial change and water security; space weather; and tracking wildlife from space. The BAS AI Lab also lead projects under the Alan Turing Institute AI for Science and Government research programme, including Understanding Arctic sea ice loss and Improving tracking of iceberg populations in the Southern Ocean. Through our PhD student projects we also collaborate closely with Google DeepMind, World Wildlife Fund, Max Fordham, Mott MacDonald and the UK Met Office.

PhD opportunities 

• Centre for Doctoral Training (CDT) in the Application of Artificial Intelligence to the study of Environmental Risks

Current PhD Student Projects

• Rachel Furner, BAS/Univ. Cambridge, Industry partner – Google DeepMind
  • New modelling tools for addressing computationally challenging climate science problems involving the ocean carbon cycle (2018-)
• Prem Gill, BAS/Univ. Cambridge, Industry partner – World Wildlife Fund (WWF)
  • Seals from Space: the study of Antarctic ice seals by remote sensing (2018-)
• Jon Rosser, BAS/Univ. Cambridge, Industry partner – UK Met Office
  • Causal inference techniques to tackle climate challenges (2019-)
• Risa Ueno, BAS/Univ. Cambridge, Industry partner – Max Fordham
  • Machine learning for Megacities: Understanding the impact of future climate extremes on energy resilience (2018-)

Featured reports

• The uncertain unicycle that taught itself and how it’s helping AI make good decisions
• Machine learning: the power and promise of computers that learn by example