UKRI Centre for Doctoral Training in Machine Intelligence for Nano-electronic Devices and Systems

Lead Research Organisation: University of Southampton
Department Name: Sch of of Electronics and Computer Sci


The UKRI Centre for Doctoral Training in Machine Intelligence for Nano-electronic Devices and Systems (MINDS-CDT) will operate as a centre of training excellence in the next generation of systems that employ Artificial Intelligence (AI) algorithms in low-cost/low-power device technologies: hardware-enabled AI. The use of AI in real-world applications through systems of interconnected devices (so-called Internet of Things) is increasingly important across the global economy. Various market surveys estimate the sector to be valued in the hundreds of billions, and project levels of compound annual growth of 25-30%. Applications of these technologies include smart cities, industrial IoT and robotics, connected health and smart homes. It is widely agreed that new advances in artificial intelligence and machine learning are key to unlocking the potential of these systems. Significant challenges remain, however, in the development of robust algorithms and coordinated systems that are efficient, secure, and work in concert with modern devices.

Advances in electronics will soon hit atomic scales, requiring new approaches if we are to continue to improve hardware speed and power consumption. Novel nanotechnologies such as memristors have the potential to play a key role in addressing these challenges, but critical to their employment in real-world applications is how algorithms work in the context of device physics. Further, there are significant challenges around how resources available to devices (energy, memory, etc.) can more effectively adapt to the computational tasks at hand, again requiring us to think about how hardware and software work together. The MINDS CDT is unique in its cross-disciplinary research programme crossing emerging AI algorithms and models with advances in device technologies that underpin and enable their potential. To quote from one of our industry partners, "innovation is to come from software and hardware co-development" and that "this joined-up thinking as a potential game changer".

The MINDS-CDT will train a substantial number of experts with the knowledge and skills to lead the development of this next generation of intelligent, embedded systems. The training programme will draw from both computer science and electronics expertise at the University of Southampton, and a substantial network of stakeholders from across industry, government and the broader economy. Core to our training ethos is the up-front investigation of the potential impacts of technological innovation on society, security and safety, and in the engagement of interest groups and the public in understanding the benefits as well as the risks of the use of these new developments in AI and technology for our society and economy. The processes we will use here include that all projects and research activities will be informed by in-depth impact assessment, and we will instigate an ambassadors programme for public engagement and, in particular, the engagement of underrepresented groups in AI and engineering.

Planned Impact

Key beneficiaries include:

1. The students funded through the CDT programme, and the wider research student community, both at the University of Southampton and across other EPSRC/UKRI CDT investments.

2. Industry and government partners who have significant demand for research expertise that crosses the electronics, algorithms and systems boundaries, and will draw significant benefits from the exchange of knowledge and practice.

3. Members of the public, who may have preconceptions of the benefits of AI and nanoelectronics research, with whom we will contribute to wider understanding of how these innovations can have positive impact on society.

How will they benefit?

1. Students enrolled on the programme will benefit from the perspectives brought to their training from across disciplines, from the extensive range of industry partners involved with the centre, and access to world-leading facilities. They will also receive significant benefits from the outreach activities organised, the ambassadors programme, and training in influencing public policy and entrepreneurship. The students will receive training, mentoring and feedback from impact acceleration organisations, including SETsquared, FutureWorlds and the IP Group of investors. This will give them the opportunity to engage in a series successively deeper impact creation activities, alongside their studies. These activities include patent writing, market discovery, business model development, investment pitching and spin-out creation. It is important to note that the MINDS-CDT students will not work in a bubble, isolated from the wider PGR community. They will both benefit from existing networking, training and social activities (e.g. through the Alan Turing Institute,, and the Centres of Machine Intelligence,, and IoT and Pervasive Systems,, and), and other students not funded through the centre will be able to access aspects of training pioneered through the centre. For example, we envisage the ambassadors programme to be initiated through the centre, but rolled out more broadly.

2. The vision for this CDT proposal has been co-developed with a number of industry partners from across a variety of sectors, and hence it is natural that they will be important beneficiaries from it. Industry partners, and partners from government agencies such as Dstl will be engaged from the first 12 months' taught component by, for example, co-developing challenges for group project activities. Their input to the co-development and co-supervision of research projects is also an important element of the programme. In order to maximise these benefits, we will operate a co-funding strategy with industry, using standard agreements for the management of intellectual property and norms for co-supervision arrangements. The early engagement with industry partners in developing projects is key to this. Industry and government partners will also benefit significantly through the translation of innovative practice through co-supervision.

3. Our range of outreach activities and the ambassadors programme will provide a strong focus for engagement with the public in developing a better understanding of the advantages of advances in embedded, ubiquitous AI-driven systems. How these systems benefit society through, for example, smart cities or smart (care)home applications can help to address concerns of the effects that AI will have in their lives. We also believe that this public engagement strategy can help to break down barriers and stereotypes to support the agenda of broadening participation in AI, electronics and STEM subjects in general.


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Studentship Projects

Project Reference Relationship Related To Start End Student Name
EP/S024298/1 31/03/2019 29/09/2027
2281466 Studentship EP/S024298/1 25/09/2019 29/09/2023 Jack Williamson
2280891 Studentship EP/S024298/1 25/09/2019 29/09/2023 Christopher Subia-Waud
2281492 Studentship EP/S024298/1 25/09/2019 29/09/2023 Thomas Graham Kelly
2281571 Studentship EP/S024298/1 25/09/2019 29/09/2023 Sulaiman Sadiq
2281595 Studentship EP/S024298/1 25/09/2019 29/09/2023 Hsuan-Yang Wang
2280907 Studentship EP/S024298/1 25/09/2019 29/09/2023 Jack Dymond
2488182 Studentship EP/S024298/1 23/09/2020 29/09/2024 Caterina Anna Sbandati
2488092 Studentship EP/S024298/1 23/09/2020 29/09/2024 Charles Hutchins
2488140 Studentship EP/S024298/1 23/09/2020 29/09/2024 Matthew Pugh
2488258 Studentship EP/S024298/1 23/09/2020 29/09/2024 Alexander-Hanyu Wang
2488215 Studentship EP/S024298/1 23/09/2020 29/09/2024 Kian Spencer
2488103 Studentship EP/S024298/1 23/09/2020 29/09/2024 Ilias Kazantzidis
2488257 Studentship EP/S024298/1 23/09/2020 29/09/2024 Mark Towers
2488135 Studentship EP/S024298/1 23/09/2020 29/09/2024 Alexander Lowe
2488218 Studentship EP/S024298/1 23/09/2020 29/09/2024 Elliot Stein
2488130 Studentship EP/S024298/1 23/09/2020 29/09/2024 Olaf Leszek Lipinski
2482600 Studentship EP/S024298/1 27/09/2020 29/09/2024 Madeleine Charlotte Dwyer
2482491 Studentship EP/S024298/1 27/09/2020 29/09/2024 Ahmet Cirakoglu
2482601 Studentship EP/S024298/1 27/09/2020 29/09/2024 Harry Horler
2482465 Studentship EP/S024298/1 27/09/2020 29/09/2024 Jennifer Anthony Barnes-Nunn
2482571 Studentship EP/S024298/1 27/09/2020 29/09/2024 Matthew George Durrant
2482453 Studentship EP/S024298/1 27/09/2020 29/09/2024 Callum Aitchison
2619114 Studentship EP/S024298/1 29/09/2021 29/09/2025 Nikolaos Chazaridis
2693178 Studentship EP/S024298/1 29/09/2021 29/09/2025 Kryspin Varys
2693164 Studentship EP/S024298/1 29/09/2021 29/09/2025 Carl Richardson
2693114 Studentship EP/S024298/1 29/09/2021 29/09/2025 Shafiullah Rahman
2616639 Studentship EP/S024298/1 29/09/2021 29/09/2025 Epifanios Baikas
2693039 Studentship EP/S024298/1 29/09/2021 29/09/2025 Balint Gucsi
2616683 Studentship EP/S024298/1 29/09/2021 30/09/2025 John William Birkbeck
2693112 Studentship EP/S024298/1 29/09/2021 29/09/2025 Arezou Nayebi
2693047 Studentship EP/S024298/1 29/09/2021 29/09/2025 Kieran Alexander Maguire
2693042 Studentship EP/S024298/1 29/09/2021 29/09/2025 Shannon How
2749426 Studentship EP/S024298/1 23/09/2022 29/09/2026 Jack Ryan
2748895 Studentship EP/S024298/1 23/09/2022 29/09/2026 Rudra Mutalik
2748021 Studentship EP/S024298/1 23/09/2022 29/09/2026 Oliver Edward Grainge
2749419 Studentship EP/S024298/1 23/09/2022 29/09/2026 Keniel Romario Peart
2747979 Studentship EP/S024298/1 23/09/2022 29/09/2026 Tyler James Clark
2748884 Studentship EP/S024298/1 23/09/2022 29/09/2026 William Hunt
2749498 Studentship EP/S024298/1 23/09/2022 29/09/2026 Mark Saunders