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
Abstract
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.
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.
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.
Organisations
- University of Cambridge, United Kingdom (Lead Research Organisation)
- Impax Asset Management (Project Partner)
- ICCCAD (Project Partner)
- Marks and Spencer, United Kingdom (Project Partner)
- Myrtle Software (Project Partner)
- Dept for Env Food & Rural Affairs DEFRA, United Kingdom (Project Partner)
- Natural England, United Kingdom (Project Partner)
- Frontier Development Lab (Project Partner)
- Allstate (Project Partner)
- DeepMind (Project Partner)
- ESA/ESRIN (Project Partner)
- HSBC Bank plc, United Kingdom (Project Partner)
- World Conservation Monitoring Ctr WCMC (Project Partner)
- MAX Fordham & Partners, United Kingdom (Project Partner)
- Mott Macdonald UK Ltd, United Kingdom (Project Partner)
- The Mathworks Ltd, United Kingdom (Project Partner)
- Mission Control for Earth (Project Partner)
- Total American Services (Project Partner)
- Dept for Business, Innovation and Skills, United Kingdom (Project Partner)
- Descartes Labs (Project Partner)
- Cambridge Spark (Project Partner)
- Jane Street Europe (Project Partner)
- Esri, United States (Project Partner)
- Buro Happold Limited, United Kingdom (Project Partner)
- Isaac Newton Inst for Mathematical Sci (Project Partner)
- Risk Management Solutions Ltd, United Kingdom (Project Partner)
- Anglian Water (Project Partner)
- B P International Ltd, United Kingdom (Project Partner)
- Microsoft Corporation (USA), United States (Project Partner)
- European Bank for Reconstruction and Dev, United Kingdom (Project Partner)
- Friends of The Earth (Project Partner)
- Environment Agency, United Kingdom (Project Partner)
- Centre for Env Fisheries Aqua Sci CEFAS, United Kingdom (Project Partner)
- Met Office, United Kingdom (Project Partner)
- Schlumberger Cambridge Research Ltd, United Kingdom (Project Partner)
- Towers Watson (Project Partner)
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 |
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 |