Artificial Intelligence Lab

Artificial Intelligence Lab

The BAS AI Lab is a cross-disciplinary group of scientists and engineers leading in the application of AI and Data Science methods to tackle our greatest polar research challenges.

AI methods are now embedded across many areas of BAS science and engineering, including: oceanography; climate science and weather extremes; glacial change and water security; space weather monitoring; and for tracking icebergs and wildlife from space. The Lab has two overarching objectives: developing AI algorithms for optimising the use of our polar research vessels, our fleet of underwater and aerial vehicles, and Antarctic research bases; and the development of machine learning methods for understanding and predicting environmental change. The BAS AI Lab also lead projects under The Alan Turing Institute’s 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 several industrial partners including Google DeepMind, Microsoft, World Wildlife Fund, Max Fordham, Mott MacDonald and the UK Met Office.

BAS AI Lab Themes

PhD opportunities 

Current PhD Student Projects

Machine Learning Workshop 2019
Machine Learning for Environmental Sciences Workshop and Hackathon, BAS, June 2019 (blog post)

Ellen Bowler

Researcher in Machine Learning

James Byrne

IT Research Software Engineer

BAS IT team

Maria Fox

Principal Researcher in Environmental AI

Peter Fretwell

Geographic Information Officer

Mapping and GIS team

Amie Jackson

Business Change Manager

Dan Jones

Physical Oceanographer (Adjoint Modelling)

Polar Oceans team

Andrew Meijers

Deputy Science Leader, Polar Oceans

Polar Oceans team

Tracy Moffat-Griffin

Deputy Science Leader - Atmospheric Scientist VC

Atmosphere, Ice and Climate team

Tony Phillips

Climate Model Data and Analysis Software Manager

Atmosphere, Ice and Climate team

Martin Rogers

Researcher in Machine Learning


  • Co-Leaders: Maria Fox and  Scott Hosking
  • Project Management: Elaina Ford, Sarah Berry
  • Steering Group: Rachel Cavanagh, Andrew Fleming, Mervyn Freeman, Scott Hosking, Amie Jackson, Dan Jones, Tracy Moffat-Griffin, Ana Pereira-O’Callaghan, Alex Tate

Co-Supervised and Affiliated Students

Michelle Wan (AI for Environmental Risks, CDT) | Fruzsina Agocs (Kavli Institute for Cosmology, Univ. Cambridge) | Matt Amos (Univ. Lancaster) | Robert Rouse (Future Infrastructure and Built Environment CDT, Univ. Cambridge) | Will Tebbutt (Machine Learning Group, Univ. Cambridge) | Simon Thomas (Univ. Cambridge)

Former Members

Ellie Krige (Part III Project, Univ. Cambridge, 2020-2021), Tudor Suciu and Mala Virdee (MRes projects in AI for Environmental Risks, CDT, 2020), Shahel Khan (Part III Project, Univ. Cambridge, 2017-2018), Stratis Markou (Internship, Machine Learning Group, Cambridge, 2017), Lille Borresen (Internship, 2018), Daniel Popa-Christobal (Internship, 2018), Harry Holt (paper, Internship, 2017)

AI for Environmental Sciences

21 July, 2019 by Rachel Furner

Rachel Furner is a PhD student at British Antarctic Survey, which has recently opened up its new AI Lab, that aims to foster the application of various machine learning (and …

Using AI to track whales from space

4 February, 2021

British Antarctic Survey (BAS) scientists will work with an Artificial Intelligence company after being awarded a contract from the Canadian Space Agency (CSA) to support the protection of an endangered …

BAS participates in EGU General Assembly 2020

4 May, 2020

As the world continues to work around lockdown, the EGU General Assembly 2020 will take place this week (4-8 May) online. The annual EGU (European Geosciences Union) meeting, which usually …

PhD centre will nurture new leaders in Earth observation

9 January, 2020

A new centre will enable 50 fully-funded PhD researchers to harness satellite data to tackle global environmental challenges. The Centre for Satellite Data in Environmental Science (SENSE) will bring together expertise in …

Using AI to help tackle global environmental challenges

26 February, 2019

A new Centre for Doctoral Training, involving researchers from British Antarctic Survey, will develop Artificial Intelligence (AI) techniques to address critical environmental challenges. Climate change and environmental hazards pose some …

Watching whales from space

1 November, 2018

Scientists have used detailed high-resolution satellite images provided by Maxar Technologies’ DigitalGlobe, to detect, count and describe four different species of whales. Reported this week in the journal Marine Mammal …

FEATURED PAPER: Temperature change in Sichuan

13 November, 2017

The Sichuan basin is one of the most densely populated regions of China. Along with insufficient arable land and economic underdevelopments, this region is particularly vulnerable to climate-related stresses. Improving …