Turing AI Fellowship: AI for Intelligent Neurotechnology and Human-Machine Symbiosis
Lead Research Organisation:
University of Bath
Department Name: Computer Science
Abstract
Wearable neurotechnology utilization is expected to increase dramatically in the coming years, with applications in enabling movement-independent control and communication, rehabilitation, treating disease and improving health, recreation and sport among others. There are multiple driving forces:- continued advances in underlying science and technology; increasing demand for solutions to repair the nervous system; increase in the ageing population worldwide producing a need for solutions to age-related, neurodegenerative disorders, and "assistive" brain-computer interface (BCI) technologies; and commercial demand for nonmedical BCIs. There is a significant opportunity for the UK to lead in the development of AI-enabled neurotechnology R&D.
There are a number of key challenges to be addressed, mainly associated with the complexity of signals measured from the brain. AI has the potential to revolutionise the neurotechnology industry and neurotechnology presents an excellent challenge for AI. This fellowship will build on the award-winning AI and neurotechnology research of the fellow and offer real potential for impact through established clinical partnerships and in the neurotechnology industry.
The objective of this project is to build on award-winning AI and neurotechnology R&D to address key shortcomings of neurotechnology that limit its widespread use and adoption using a range of key neural network technologies in a state-of-the-art framework for processing neural signals developed by the proposed fellow.
The AI technologies developed for neurotechnology will be applied across sectors to demonstrate translational AI through engagement with at least 10 companies across at least 5 sectors during the fellowship, to demonstrate societal and economic benefit and interdisciplinary and translational AI skills development. The project has multiple industry, clinical and academic partners and is expected to produce world-leading AI technologies and propel the fellow to world-leading status in developing AI for neurotechnology which will impact widely.
A major focus of the project is ensuring the expectations of the fellow role are met. This includes:-
-Ensuring the processes and resources are in place to build a world-leading profile by the end of the fellowship;
-Focusing on planning research of the team as new results emerge and hypothesis are tested, to refine and develop a high-quality programme of ambitious, novel and creative research, in AI-enabled Neurotechnology. Specific focus will be ensuring meticulous planning, execution and follow-up to produce world-leading results;
-Continuing to perform my leadership role as director of the ISRC and leader of the data analytics theme, expanding the team and actively seek to develop into a position of higher leadership of the research agenda at Ulster, and in the national and international research community;
-Focusing on strengthening relationships and collaborations with colleagues in industry and academia, and maximising the potential for flexible career paths for researchers within the team
-Acting as an ambassador and advocate for AI, science and ED&I including by continuing to actively provide opinions and engaging with questions around AI and ethics, and responsible research and innovation (RRI). A focus will be embedding this throughout the activities of the fellowship but across the region and internationally;
-Seeking to engage with and influence the strategic direction of the UK AI research and innovation landscape through engagement with their peers, policymakers, and other stakeholders including the public through.
-Ensuring that the fundamental research is developed to have a high likelihood of impact on UK society/economy through trials across a range of patient groups to develop the evidence base and transfer of intellectual property to products, in particular through NeuroCONCISE Ltd, a main project partner.
There are a number of key challenges to be addressed, mainly associated with the complexity of signals measured from the brain. AI has the potential to revolutionise the neurotechnology industry and neurotechnology presents an excellent challenge for AI. This fellowship will build on the award-winning AI and neurotechnology research of the fellow and offer real potential for impact through established clinical partnerships and in the neurotechnology industry.
The objective of this project is to build on award-winning AI and neurotechnology R&D to address key shortcomings of neurotechnology that limit its widespread use and adoption using a range of key neural network technologies in a state-of-the-art framework for processing neural signals developed by the proposed fellow.
The AI technologies developed for neurotechnology will be applied across sectors to demonstrate translational AI through engagement with at least 10 companies across at least 5 sectors during the fellowship, to demonstrate societal and economic benefit and interdisciplinary and translational AI skills development. The project has multiple industry, clinical and academic partners and is expected to produce world-leading AI technologies and propel the fellow to world-leading status in developing AI for neurotechnology which will impact widely.
A major focus of the project is ensuring the expectations of the fellow role are met. This includes:-
-Ensuring the processes and resources are in place to build a world-leading profile by the end of the fellowship;
-Focusing on planning research of the team as new results emerge and hypothesis are tested, to refine and develop a high-quality programme of ambitious, novel and creative research, in AI-enabled Neurotechnology. Specific focus will be ensuring meticulous planning, execution and follow-up to produce world-leading results;
-Continuing to perform my leadership role as director of the ISRC and leader of the data analytics theme, expanding the team and actively seek to develop into a position of higher leadership of the research agenda at Ulster, and in the national and international research community;
-Focusing on strengthening relationships and collaborations with colleagues in industry and academia, and maximising the potential for flexible career paths for researchers within the team
-Acting as an ambassador and advocate for AI, science and ED&I including by continuing to actively provide opinions and engaging with questions around AI and ethics, and responsible research and innovation (RRI). A focus will be embedding this throughout the activities of the fellowship but across the region and internationally;
-Seeking to engage with and influence the strategic direction of the UK AI research and innovation landscape through engagement with their peers, policymakers, and other stakeholders including the public through.
-Ensuring that the fundamental research is developed to have a high likelihood of impact on UK society/economy through trials across a range of patient groups to develop the evidence base and transfer of intellectual property to products, in particular through NeuroCONCISE Ltd, a main project partner.
Organisations
- University of Bath (Lead Research Organisation)
- NVIDIA Limited (UK) (Project Partner)
- University of Rwanda (Project Partner)
- Seagate Technology (Ireland) (Project Partner)
- KNOWLEDGE TRANSFER NETWORK LIMITED (Project Partner)
- Allstate (Project Partner)
- Trinity College Dublin (Project Partner)
- National Rehabilitation Hospital (Project Partner)
- Etexsense (Project Partner)
- Florida Atlantic University (Project Partner)
- Barnsley Hospital NHS Foundation Trust (Project Partner)
- Dell Corporation Ltd (Project Partner)
- NeuroCONCISE (Project Partner)
Publications

Ahmed S
(2023)
Knowledge-based Intelligent System for IT Incident DevOps

Ahmed S
(2023)
An Empirical Analysis of State-of-Art Classification Models in an IT Incident Severity Prediction Framework
in Applied Sciences

Arpaia P
(2023)
Visual and haptic feedback in detecting motor imagery within a wearable brain-computer interface
in Measurement

Arpaia P
(2023)
Paving the Way for Motor Imagery-Based Tele-Rehabilitation through a Fully Wearable BCI System.
in Sensors (Basel, Switzerland)


Sanchez-Bornot J
(2024)
Solving large-scale MEG/EEG source localisation and functional connectivity problems simultaneously using state-space models.
in NeuroImage


Tortora S
(2023)
Effect of Lower Limb Exoskeleton on the Modulation of Neural Activity and Gait Classification.
in IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Related Projects
Project Reference | Relationship | Related To | Start | End | Award Value |
---|---|---|---|---|---|
EP/V025724/1 | 01/01/2021 | 01/02/2023 | £1,823,387 | ||
EP/V025724/2 | Transfer | EP/V025724/1 | 02/02/2023 | 01/01/2026 | £1,199,266 |
Description | We have enabled a spinal injured athlete to compete at the international Cybathlon competition |
First Year Of Impact | 2024 |
Sector | Healthcare |
Impact Types | Cultural Societal |
Description | Invited Speaker : Royal Hospital of Neurodisability Conf. on Interventions in DOC, London 2023 |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | Regional |
Primary Audience | Professional Practitioners |
Results and Impact | Royal Hospital of Neurodisability Conference on Interventions in Disorders of Consciousness , London 2023 |
Year(s) Of Engagement Activity | 2023 |
URL | https://www.rhn.org.uk/events/interventions-in-disorders-of-consciousness/ |
Description | Invited speaker: ISRC Computational Neuroscience, Neurotechnology and Neuroinspired AI (CN3) Autumn School (Derry), 2023 |
Form Of Engagement Activity | Participation in an activity, workshop or similar |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Third sector organisations |
Results and Impact | Autumn school |
Year(s) Of Engagement Activity | 2023 |
URL | https://www.ulster.ac.uk/faculties/computing-engineering-and-the-built-environment/computing-enginee... |
Description | Invited speaker: Neuroinformatics, Neural Networks and Neurocomputers Summer School (Bulgaria, online), 2023; |
Form Of Engagement Activity | Participation in an activity, workshop or similar |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Third sector organisations |
Results and Impact | Summer School - online |
Year(s) Of Engagement Activity | 2023 |
URL | https://www.knowledgeengineering.ai/summer-school |
Description | Invited speaker: The Royal Society Neural Interface Summit, (London), 2023 |
Form Of Engagement Activity | Participation in an activity, workshop or similar |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Professional Practitioners |
Results and Impact | A summit on Neural Interfaces which engaged a broad audience and will results in a follow report by the Royal Society |
Year(s) Of Engagement Activity | 2023 |
URL | https://royalsociety.org/science-events-and-lectures/2023/09/royal-society-neural-interfaces-summit-... |
Description | Invited speaker: the AI & ML Showcase event (Bath), 2023; |
Form Of Engagement Activity | Participation in an activity, workshop or similar |
Part Of Official Scheme? | No |
Geographic Reach | Local |
Primary Audience | Third sector organisations |
Results and Impact | AI showcase vent |
Year(s) Of Engagement Activity | 2023 |
URL | https://www.bath.ac.uk/events/the-unreasonable-effectiveness-of-machine-learning-in-pretty-much-ever... |