UKRI Centre for Doctoral Training in Environmental Intelligence: Data Science & AI for Sustainable Futures

Lead Research Organisation: University of Exeter
Department Name: Mathematics


The vision of this CDT is to enhance society's resilience to changes in our environment through the development of Environmental Intelligence (EI): using the integration of data from multiple inter-related sources and Artificial Intelligence (AI) to provide evidence for informed decision-making, increase our understanding of environmental challenges and provide information that is required by individuals, policy-makers, institutions and businesses.

Many of the most important problems we face today are related to the environment. Climate change, healthy oceans, water security, clean air, biodiversity loss, and resilience to extreme events all play a crucial role in determining our health, wealth, safety and future development. The UN's 2030 Agenda for Sustainable Development calls for a plan of action for people, planet and prosperity, aiming to take the bold and transformative steps that are urgently needed to shift the world onto a sustainable and resilient path. Developing a clear understanding of the challenges and identifying potential solutions, both for ourselves and our planet, requires high quality, accessible, timely and reliable data to support informed decision making. Beyond the quantification of the need for change and tracking developments, EI has another important role to play in facilitating change through integration of cutting edge AI technology in energy, water, transport, agricultural and other environmentally-related systems and by empowering individuals, organisations and businesses through the provision of personalized information that will support behavioural change.

Students will receive training in the range of skills they will require to become leaders in EI: (i) the computational skills required to analyse data from a wide variety of sources; (ii) environmental domain-specific expertise; (iii) an understanding of governance, ethics and the potential societal impacts of collecting, mining, sharing and interpreting data, together with the ability to communicate and engage with a diverse range of stakeholders. The training programme has been designed to be applicable to students with a diverse range of backgrounds and experiences.

Graduates of the CDT will be equipped with the skills they need to become tomorrow's leaders in identifying and addressing interlinked, social, economic and environmental risks. Having highly trained individuals with a wide range of expertise, together with the skills to communicate with a diverse range of stakeholders and communities, will have far reaching impact across a wide number of sectors. Traditionally, PhD students trained in the technical aspects of AI have been distinct from those trained in policy and business implementation. This CDT will break that mould by integrating students with a diverse range of backgrounds and interests and providing them with the training, in conjunction with external partners, that will ensure that they are well versed in both cutting edge methodology and on the ground policy and business implementation.

The University of Exeter's expertise in inter- and trans-disciplinary environmental, climate, sustainability, circular economy and health research makes it uniquely placed to lead an inter-disciplinary CDT that will pioneer the use of AI in understanding the complex interactions between the environment, climate, natural ecosystems, human social and economic systems, and health. Students will benefit from the CDTs strong relationships with its external partners, including the Met Office. Many of these partners are employers of doctoral graduates in AI and see an increasing need for employees with skills from across multiple disciplines. Their involvement in the planning and ongoing management of the CDT will ensure that, in this rapidly changing domain, the CDT delivers leading-edge research that will enable partners and others to participate effectively in EI and lead to optimal employment opportunities for its graduates.

Planned Impact

The core aim of the UKRI CDT in Environmental Intelligence (EI) is "To provide industry, government and academia with a community of highly-trained scientists with the skills and expertise to apply Artificial Intelligence (AI) to a wide range of environmental and sustainability challenges". Through a world-class research training experience, PhD students will be equipped with the skills required to transform the EI market. Their multi-disciplinary education in the application of AI to environmental challenges, and exposure to real-world challenges from across the public and private sectors, will enable them to have far-reaching influence on decision making across all sectors.

The market for EI is currently ill-defined due to its cross-cutting nature. Sectors reliant on the provision of environmental data and its subsequent transformation into actionable intelligence include Energy, Food, Infrastructure Development, Re/Insurance and Environmental Policy; however, the increasing requirement for all sectors to participate in collective environmental action means that there is an emerging need for EI skills within these and other sectors. Examples include the requirement for carbon reporting and climate risk disclosure within the financial sector, and the requirement to understand environmental factors in the preventative healthcare sector.

Recognising the importance of the interrelationship between AI & Data Driven Economies and Clean Growth, and the associated opportunities, the UK Industrial Strategy[1] notes that "Action to support our first Grand Challenge [sic: AI and the Data Driven Economy - putting the UK at the forefront of the AI and data revolution] will complement the second challenge we have identified - maximising the advantages to UK industry of the global shift to clean growth". The primary impact of this CDT will be provision of a robust supply of skilled scientists and knowledge that enables industry and government to deliver this grand vision.

Underpinning this will be three primary pathways to impact:

SKILLS & KNOWLEDGE GENERATION: Students within the CDT will work collaboratively with academic researchers, industry and government to address cutting-edge research challenges that cross multiple disciplines and enable the use of AI to address some of the most pressing challenges facing society today and in the future. The CDT will optimise the impact of such knowledge generation by training its students in knowledge exchange activities, and effective research co-creation and collaboration. In addition to direct participation of industry and government organisations, the CDT will work with appropriate knowledge dissemination bodies such as Knowledge Transfer Networks.

STRENGTH IN PLACES: By building upon regional strengths as identified in the South West Science and Innovation Audit[2] the CDT will support continued development of the labour market that feeds the Environmental Resilience & Digital Innovation clusters within the South West, and in turn continued economic growth within the region.

INTERNATIONAL IMPACT: The skills developed and research challenges addressed by the CDT will support UK Government's aspirations to ensure that the UK is placed as a world-leading knowledge economy[3]. International collaboration will play a core role in the delivery of the CDT, and will facilitate delivery of enhanced reputational benefits. International collaborators will include global organisations such as the World Health Organization, as well as drawing upon University of Exeter's strategic academic collaborations, for example with the Chinese University of Hong Kong.

[1] p41
[3] p67


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Studentship Projects

Project Reference Relationship Related To Start End Student Name
EP/S022074/1 01/06/2019 30/11/2027
2480625 Studentship EP/S022074/1 01/10/2019 30/09/2023 Timothy Lam
2238270 Studentship EP/S022074/1 01/10/2019 30/09/2023 Guy Lomax
2238174 Studentship EP/S022074/1 01/10/2019 08/05/2025 Margaret Bolton
2238262 Studentship EP/S022074/1 01/10/2019 30/09/2023 Arthur Vandervoort
2238169 Studentship EP/S022074/1 01/10/2019 30/09/2023 Liam Berrisford
2246311 Studentship EP/S022074/1 01/10/2019 15/11/2023 Christopher Kerry
2238178 Studentship EP/S022074/1 01/10/2019 30/09/2023 Aydan Westwood
2238163 Studentship EP/S022074/1 01/10/2019 16/12/2023 Joshua Alexander Redmond
2238180 Studentship EP/S022074/1 01/10/2019 04/01/2024 Eliza Kate Duncan
2238254 Studentship EP/S022074/1 01/10/2019 30/09/2023 Alice Florence Wells
2401434 Studentship EP/S022074/1 01/10/2020 30/09/2024 Frederica Poznansky
2398846 Studentship EP/S022074/1 01/10/2020 30/09/2024 Daneen Cowling
2398952 Studentship EP/S022074/1 01/10/2020 30/09/2024 Sara Sjosten
2399019 Studentship EP/S022074/1 01/10/2020 30/09/2024 Nicola Wilson
2398854 Studentship EP/S022074/1 01/10/2020 30/09/2024 Elizabeth Georgia Galloway
2397152 Studentship EP/S022074/1 01/10/2020 30/09/2024 Ian Burton
2397154 Studentship EP/S022074/1 01/10/2020 30/09/2024 Emma Bailey
2398900 Studentship EP/S022074/1 01/10/2020 30/09/2024 Patrycja Ewa Nowak
2398866 Studentship EP/S022074/1 01/10/2020 30/09/2024 Abhiraami Navaneethanathan
2398938 Studentship EP/S022074/1 01/10/2020 30/09/2024 William Montgomery Sant
2576373 Studentship EP/S022074/1 01/10/2021 30/09/2025 CESAR ARTURO ANGELES RUIZ
2589283 Studentship EP/S022074/1 01/10/2021 30/09/2025 Jonathan Luke Growcott
2585378 Studentship EP/S022074/1 01/10/2021 30/09/2025 Thomas Hogger-Gadsby
2589174 Studentship EP/S022074/1 01/10/2021 30/09/2025 Owain Lewis Harris
2576260 Studentship EP/S022074/1 01/10/2021 30/09/2025 EMILY ROBINSON
2576402 Studentship EP/S022074/1 01/10/2021 30/09/2025 MANJU BURA
2576778 Studentship EP/S022074/1 01/10/2021 30/09/2025 BENJAMIN FITKOV-NORRIS
2576992 Studentship EP/S022074/1 01/10/2021 30/09/2025 NATHANAEL SHEEHAN
2576436 Studentship EP/S022074/1 01/10/2021 30/09/2025 JAKE CURRY
2576457 Studentship EP/S022074/1 01/10/2021 30/09/2025 ELEANOR FOX