Artificial Intelligence utilizing Space assets for Science discovery

Brief description of the context of the research including potential impact
The 2017-2027 Decadal Survey for Earth Science Applications from Space finding 1.1 states that Space-based Earth Observations provide a global perspective of Earth that has transformed our "scientific understanding" of our planet, and the vantage point of space enables us to see the extent to which Earth's ever-changing processes influence our lives. However, the volume of data generated daily by Earth Observation (EO) satellites is far too great for humans to conceivably digest, analyze, and synthesize into meaningful decisions and strategies for climate change mitigation and disaster preparedness. The use of Artificial Intelligence (AI) in combination with space assets can maximize the scientific return of space missions through revealing new connections, aid in autonomous decision making, and improve scientific understanding of complex relationships between ecosystems.
Aims and Objectives
The aims of this PhD research are to utilize space-based assets for scientific research related to climate disaster mitigation, preparedness and response, and aid in scientific understanding through the use of AI. Deep Learning will be explored in this work, which can unveil previously unknown relationships through extracting information from highly-dimensional data via convolutional neural network architectures to learn spatiotemporal features from timeseries EO datasets. Interpretability and uncertainty quantification of models will also be explored in this work. Interpretability is important as it is crucial to be able to effectively communicate how models generate predictions to stakeholders, policy makers, and governments, as these entities are less likely to adopt these AI solutions as reliable if not clearly understood.
Novelty of the research methodology
The novelty of this research will be the identification and formulation of AI and Machine Learning models that can be applied across scientific domains and use cases. The focus on model explainability, interpretability, and uncertainty is at the beginning stages of exploration for researchers within the AI for EO field, which will be critical to implementing these technologies for real-world use.
Alignment to EPSRC's strategies and research areas
This research aligns with multiple EPSRC research areas, namely Artificial intelligence
technologies, operational research, and the UK climate resilience program.
Any companies or collaborators involved

The PhD work will be supervised by Professor Yarin Gal and Senior Research Fellow Freddie Kalaitzis. Collaborations with the Satellite Applications Catapult and Deimos Space through an industrial studentship will provide EO expertise to support the research

AIMS's impact will be felt across domains of acute need within the UK. We expect AIMS to benefit: UK economic performance, through start-up creation; existing UK firms, both through research and addressing skills needs; UK health, by contributing to cancer research, and quality of life, through the delivery of autonomous vehicles; UK public understanding of and policy related to the transformational societal change engendered by autonomous systems.

Autonomous systems are acknowledged by essentially all stakeholders as important to the future UK economy. PwC claim that there is a £232 billion opportunity offered by AI to the UK economy by 2030 (10% of GDP). AIMS has an excellent track record of leadership in spinout creation, and will continue to foster the commercial projects of its students, through the provision of training in IP, licensing and entrepreneurship. With the help of Oxford Science Innovation (investment fund) and Oxford University Innovation (technology transfer office), student projects will be evaluated for commercial potential.

AIMS will also concretely contribute to UK economic competitiveness by meeting the UK's needs for experts in autonomous systems. To meet this need, AIMS will train cohorts with advanced skills that span the breadth of AI, machine learning, robotics, verification and sensor systems. The relevance of the training to the needs of industry will be ensured by the industrial partnerships at the heart of AIMS. These partnerships will also ensure that AIMS will produce research that directly targets UK industrial needs. Our partners span a wide range of UK sectors, including energy, transport, infrastructure, factory automation, finance, health, space and other extreme environments.

The autonomous systems that AIMS will enable also offer the prospect of epochal change in the UK's quality of life and health. As put by former Digital Secretary Matt Hancock, "whether it's improving travel, making banking easier or helping people live longer, AI is already revolutionising our economy and our society." AIMS will help to realise this potential through its delivery of trained experts and targeted research. In particular, two of the four Grand Challenge missions in the UK Industrial Strategy highlight the positive societal impact underpinned by autonomous systems. The "Artificial Intelligence and data" challenge has as its mission to "Use data, Artificial Intelligence and innovation to transform the prevention, early diagnosis and treatment of chronic diseases by 2030". To this mission, AIMS will contribute the outputs of its research pillar on cancer research. The "Future of mobility" challenge highlights the importance the autonomous vehicles will have in making transport "safer, cleaner and better connected." To this challenge, AIMS offers the world-leading research of its robotic systems research pillar.

AIMS will further promote the positive realisation of autonomous technologies through direct influence on policy. The world-leading academics amongst AIMS's supervisory pool are well-connected to policy formation e.g. Prof Osborne serving as a Commissioner on the Independent Commission on the Future of Work. Further, Dr Dan Mawson, Head of the Economy Unit; Economy and Strategic Analysis Team at BEIS will serve as an advisor to AIMS, ensuring bidirectional influence between policy objectives and AIMS research and training.

Broad understanding of autonomous systems is crucial in making a society robust to the transformations they will engender. AIMS will foster such understanding through its provision of opportunities for AIMS students to directly engage with the public. Given the broad societal importance of getting autonomous systems right, AIMS will deliver core training on the ethical, governance, economic and societal implications of autonomous systems.