UKRI Centre for Doctoral Training in Application of Artificial Intelligence to the study of Environmental Risks (AI4ER)

Lead Research Organisation: University of Cambridge
Department Name: Earth Sciences


The UKRI Centre for Doctoral Training in "Application of Artificial Intelligence to the study of Environmental Risks" will develop a new generation of innovation leaders to tackle the challenges faced by societies across the globe living in the face of environmental risk, by developing new methods that exploit the potential of Artificial Intelligence (AI) approaches to the proper analysis of complex and diverse environmental data. It is made of multiple departments within Cambridge University, alongside the British Antarctic Survey and a wide range of partners in industry and policy. AI offers huge potential to transform our ability to understand, monitor and predict environmental risks, providing direct societal benefit as well as potential commercial opportunities. Delivering the UN 2030 Sustainable Development Agenda and COP 21 Paris Agreement present enormous and urgent challenges. Population and economic growth drive increased demands on a planet with finite resources; the planet's biodiversity is suffering increasing pressures. Simultaneously, humanity's vulnerabilities to geohazards are increasing, due to fragilities inherent in urbanisation in the face of risks such as floods, earthquake, and volcanic eruptions. Reliance on sophisticated technical infrastructures is a further exposure. Understanding, monitoring and predicting environmental risks is crucial to addressing these challenges. The CDT will provide the global knowledge leadership needed, by building partnership with leaders in industry, commerce, policy and academia in visionary, creative and cross-disciplinary teaching and research. Vast and growing datasets are now available that document our changing environment and associated risks. The application of AI techniques to these datasets has the potential to revolutionise our ability to build resilience to environmental hazards and manage environmental change. Harnessing the power of AI in this regard will support two of the four Grand Challenges identified in the UK's Industrial Strategy, namely, to put the UK at the forefront of the AI and data revolution and to maximise the advantages for UK industry from the global shift to clean growth.

The students in the CDT will be trained in a broad range of aspects of the application of AI to environmental risk in a multi- disciplinary and enthusing research setting, to become world-leaders in the arena. They will undertake media training activities, public engagement, and training in the delivery of policy advice as well as the development of entrepreneurial skills and an understanding of the approach of business to sustainability. Discussion of the broader societal, legal and ethical dimensions will be integral to this training. In this way the CDT will seed a new domain of AI application in the UK that will become a champion for the subject globally.

Planned Impact

The "Application of Artificial Intelligence to the study of Environmental Risks" (AI4ER) CDT will produce 50+ expert highly- trained scientists and engineers with a broad perspective on the application of AI to environmental challenges. They will be capable of leading the UK's development of these new technology-driven opportunities, building new innovative entrepreneurial business, engaged in policy advice and informing the wider community, and building the UK as a world- leader in the AI for environmental science domain. The students will graduate with experience of the application and development of AI to some of society's most pressing challenges, building partnerships with industrial, governmental and non-governmental bodies to deploy the methods in which they will become experts and to take leadership roles in the UK and globally.

The CDT will deliver world-class multidisciplinary research in the application of AI to a broad range of environmental risks that align with development goals, both nationally and globally, and address the needs of legislators, policy makers, industry, commerce, third-sector organisations and others for trustworthy and accessible environmental information. It will provide global knowledge leadership, by building partnership with leaders in industry, commerce, policy and academia to co-create visionary, innovative and cross-disciplinary teaching and research. The CDT will offer multiple opportunities for direct, two-way engagement with end users including through co-supervision of students with partner organisations, extended research visits to international partners through Cambridge-Africa programme and others such as the International Centre for Climate Change and Development (Bangladesh), and policy placements. These engagements will allow the sharing of knowledge and data and the co-production of ideas and tools. The close links with the Cambridge innovation space, with significant spin-out activity from existing university IP activity, put this CDT in the most advantageous place possible to translate the research to build knowledge wealth. The research output will underpin future industrial research and development and entrepreneurial innovation aimed at transforming our ability to manage environmental risks.

Within the UK, the CTD will support the policy objectives of the Industrial Strategy, the Clean Growth Strategy and the 25- year Environment Plan, and other national policy frameworks such as the Climate Change Risk Assessment. Internationally, the research results will be relevant to the delivery of the UN Sustainable Development Goals and the Sendai Framework for Disaster Risk Reduction, and will support the implementation of the Paris Agreement on Climate Change, including the Global Stocktake, including through input to the reports of the Intergovernmental Panel on Climate Change, and will feed in to other scientific assessments such as those of the Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services.

Work will be disseminated through direct implementation with industry, international development partners, and UK government policy advice. Work, methods, results and data will be made open access to allow effective dissemination of knowledge and know-how and CDT lectures and presentations will be made available online. In doing so the CDT will not only develop crucially-needed national skills in the area of the application of AI to environmental risk, it will also position the UK in a leading position in such development. Public engagement activities will showcase the research itself, and engagement activities with schools will aim to inspire a new generation of scientists and engineers.



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Studentship Projects

Project Reference Relationship Related To Start End Student Name
EP/S022961/1 01/04/2019 30/09/2027
2272557 Studentship EP/S022961/1 01/10/2019 30/09/2023 Omer Nivron
2270313 Studentship EP/S022961/1 01/10/2019 30/09/2023 Tudor Suciu
2259965 Studentship EP/S022961/1 01/10/2019 30/09/2023 Michelle Wing Wan
2270146 Studentship EP/S022961/1 01/10/2019 30/09/2023 Petr Earlston Dolezal
2270127 Studentship EP/S022961/1 01/10/2019 30/09/2023 Edward John Brown
2270412 Studentship EP/S022961/1 01/10/2019 30/09/2023 Marc Girona-Mata
2270379 Studentship EP/S022961/1 01/10/2019 30/09/2023 Kenza Tazi
2270317 Studentship EP/S022961/1 01/10/2019 30/09/2023 Raghul Parthipan
2271309 Studentship EP/S022961/1 01/10/2019 30/09/2023 Mala Virdee
2413578 Studentship EP/S022961/1 01/10/2020 30/09/2024 Simon Donald Thomas
2413334 Studentship EP/S022961/1 01/10/2020 30/09/2024 Herbie Bradley
2413574 Studentship EP/S022961/1 01/10/2020 30/09/2024 Ira Shokar
2413454 Studentship EP/S022961/1 01/10/2020 30/09/2024 Joycelyn Longdon
2413562 Studentship EP/S022961/1 01/10/2020 30/09/2024 Simon Valentin Mathis
2413373 Studentship EP/S022961/1 01/10/2020 30/09/2024 Katherine Margaret Green
2413435 Studentship EP/S022961/1 01/10/2020 30/09/2024 Sebastian Hickman
2413201 Studentship EP/S022961/1 01/10/2020 30/09/2024 Matthew John Allen
2413365 Studentship EP/S022961/1 01/10/2020 30/09/2024 Luke Scot Cullen