EPSRC Centre for Doctoral Training in Autonomous Intelligent Machines and Systems

Lead Research Organisation: University of Oxford
Department Name: Engineering Science


A growing consensus identifies autonomous systems as core to future UK prosperity, but only if the present skills shortage is addressed. The AIMS CDT was founded in 2014 to address the training of future leaders in autonomous systems, and has established a strong track record in attracting excellent applicants, building cohorts of research students and taking Oxford's world-leading research on autonomy to achieve industrial impact. We seek the renewal of the CDT to cement its successes in sustainable urban development (including transport and finance), and to extend to applications in extreme and challenging environments and smart health, while strengthening training on the ethical and societal impacts of autonomy.

Need for Training: Autonomous systems have been the subject of a recent report from the Royal Society, and an independent review from Professor Dame Wendy Hall and Jérôme Pesenti. Both reports emphatically underline the economic importance of AI to the UK, estimating that "AI could add an additional USD $814 billion (£630bn) to the UK economy by 2035". Both reports also highlight the urgency of training many more skilled experts in autonomy: the summary of the Royal Society's report states "further support is needed to build advanced skills in machine learning. There is already high demand for people with advanced skills, and additional resources to increase this talent pool are critically needed."

In contrast with pure Artificial Intelligence CDTs, AIMS places emphasis on the challenges of building end-to-end autonomous systems: such systems require not just Machine Learning, but the disciplines of Robotics and Vision, Cyber-Physical Systems, Control and Verification. Through this cross-disciplinary training, the AIMS CDT is in a unique position to provide positive economic and societal impacts for autonomous systems by 1) growing its existing strengths in sustainable urban development, including autonomous vehicles and quantitative finance, and 2) expanding its scope to the two new application pillars of extreme and challenging environments and smart health.

AIMS itself provides evidence for the strong and increasing demand for training in these areas, with an increase in application numbers from 49 to 190 over the last five years. The increase in applications is mirrored by the increase in interest from industrial partners, which has more than doubled since 2014. Our partners span all application areas of AIMS and their contributions, which include training, internships and co-supervision opportunities, will immerse our students in a variety of research challenges linked with real-world problems.

Training programme: AIMS has and will provide broad cohort training in autonomous intelligent systems; theoretical foundations, systems research, industry-initiated projects and transferable skills. It covers a comprehensive range of topics centered around a hub of courses in Machine Learning; subsequent spokes provide training in Robotics and Vision, Control and Verification, and Cyber-Physical Systems. The cohort-focused training program will equip our students with both core technical skills via weekly courses, research skills via mini and long projects, as well as transferable skills, opportunities for public engagement, and training on entrepreneurship and IP. The growing societal impacts of autonomous systems demand that future AIMS students receive explicit training in responsible and ethical research and innovation, which will be provided by ORBIT. Additionally, courses on AI ethics, safety, governance and economic impacts will be delivered by Oxford's world-leading Future of Humanity Institute, Oxford Uehiro Centre for Practical Ethics and Oxford Martin Programme on Technology and Employment.

Planned Impact

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.


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Studentship Projects

Project Reference Relationship Related To Start End Student Name
EP/S024050/1 01/10/2019 31/03/2028
2242671 Studentship EP/S024050/1 01/10/2019 30/09/2023 Jan Brauner
2243850 Studentship EP/S024050/1 01/10/2019 30/09/2023 Cong Lu
2242815 Studentship EP/S024050/1 01/10/2019 30/09/2023 James Fox
2242651 Studentship EP/S024050/1 01/10/2019 30/09/2023 Jonas Beuchert
2243855 Studentship EP/S024050/1 01/10/2019 30/09/2023 Mrinank Sharma
2242809 Studentship EP/S024050/1 01/10/2019 30/09/2023 Alec Edwards
2243853 Studentship EP/S024050/1 01/10/2019 30/09/2023 Tim Reichelt
2242819 Studentship EP/S024050/1 01/10/2019 30/09/2023 Shu Ishida
2243852 Studentship EP/S024050/1 01/10/2019 31/03/2024 Akam Rahimi
2243851 Studentship EP/S024050/1 01/10/2019 30/09/2023 Amanda Matthes
2416389 Studentship EP/S024050/1 01/10/2020 30/09/2024 Ondrej Bajgar
2420767 Studentship EP/S024050/1 01/10/2020 30/09/2024 Zheng Xiong
2420376 Studentship EP/S024050/1 01/10/2020 30/09/2024 Benjamin Ramtoula
2416682 Studentship EP/S024050/1 01/10/2020 30/09/2024 Benjamin Ellis
2420495 Studentship EP/S024050/1 01/10/2020 30/09/2024 Baskaran Sripathmanathan
2420473 Studentship EP/S024050/1 01/10/2020 30/09/2024 Lisa Schut
2416606 Studentship EP/S024050/1 01/10/2020 30/09/2024 Jonathan Carter
2416725 Studentship EP/S024050/1 01/10/2020 30/09/2024 Dominik Kloepfer
2420751 Studentship EP/S024050/1 01/10/2020 30/09/2024 Ravi Stephens
2420122 Studentship EP/S024050/1 01/10/2020 30/09/2024 Pierre Osselin
2416722 Studentship EP/S024050/1 01/10/2020 30/09/2024 Laurynas Karaziija
2416587 Studentship EP/S024050/1 01/10/2020 30/09/2024 Frederick Bickford-Smith
2420787 Studentship EP/S024050/1 01/10/2020 30/09/2024 Charig Yang
2420422 Studentship EP/S024050/1 01/10/2020 30/09/2024 Aleksandar Shtedritski
2416714 Studentship EP/S024050/1 01/10/2020 30/09/2024 Francisco Girbal Eiras