As part of an ambitious skills and talent package set out by the UK Government, the Turing AI Fellowships initiative was created in collaboration with The Alan Turing Institute. The first Turing AI Fellowship call was led by The Alan Turing Institute and the first five Turing AI fellows were announced in October 2019.
In a latest development, the UK government has announced the awardees of the second-wave of the prestigious Turing AI Acceleration Fellowships.
This will give fifteen of the UK’s top AI innovators the resources to drive forward their ground-breaking research from speeding up medical diagnosis to increasing workplace productivity.
Notably, the New Turing AI Fellowships are part of the Government’s ambition to maintain the UK’s position as a world leader in AI and support ground-breaking innovations.
Early identification of cancer with AI
Also, AI that identifies cancer early is among fifteen innovative and diverse projects backed by £20M UK government cash injection. If successful, this ground-breaking technology will enable clinicians to track cancer more accurately and help them decide at an earlier stage what treatments patients require.
According to the government, a range of other projects including research into energy-efficient data processing which would support key sectors will benefit from this new support.
The development of an “AI clinical colleague” could further support doctors by recommending the most effective drug prescriptions and doses for patients – and helping them decide the best course of action for recovery.
Science Minister, Amanda Solloway said: “The UK is the birthplace of artificial intelligence and we have a duty to equip the next generation of Alan Turings with the tools that will keep the UK at the forefront of this remarkable technological innovation. The inspirational fellows we are backing today will use AI to tackle some of our greatest challenges head-ons, transforming how people live, work and communicate, cementing the UK’s status as a world leader in AI and data.”
Digital Minister, Caroline Dinenage, said: “The UK is a nation of innovators and this government investment will help our talented academics use cutting-edge technology to improve people’s daily lives – from delivering better disease diagnosis to managing our energy needs.”
Investment in AI skills
The fellowships form part of major government investment in AI skills and research, including sixteen Centres for Doctoral Training in AI and conversion courses to train the next generation of AI experts, announced by Prime Minister Boris Johnson in October 2019.
Named after British AI pioneer Alan Turing, the £20 million fellowship scheme will be delivered by the Engineering and Physical Sciences Research Council (EPSRC), part of UK Research and Innovation (UKRI), in partnership with the Alan Turing Institute and Office for Artificial intelligence.
EPSRC Executive Chair Professor Dame Lynn Gladden said: “The Turing AI Acceleration Fellowships will support some of our leading researchers to progress their careers and develop ground-breaking AI technologies with societal impact. By enhancing collaboration between academia and industry and accelerating these transformative technologies they will help to maintain and build on the UK’s position as a world leader in AI.”
The Turing AI Acceleration Fellows are:
- Professor Damien Coyle, University of Ulster – AI for Intelligent Neurotechnology and Human-Machine Symbiosis
- Dr Jeff Dalton, University of Glasgow – Neural Conversational Information Seeking Assistant
- Dr Theo Damoulas, University of Warwick – Machine Learning Foundations of Digital Twins
- Professor Aldo Faisal, Imperial College – Reinforcement Learning for Healthcare
- Professor Yulan He, University of Warwick – Event-Centric Framework for Natural Language Understanding
- Dr Jose Miguel Hernandez Lobato, University of Cambridge – Machine Learning for Molecular Design
- Dr Antonio Hurtado, University of Strathclyde – PHOTONics for Ultrafast Artificial Intelligence
- Dr Per Lehre, University of Birmingham – Rigorous Time-Complexity Analysis of Co-evolutionary Algorithms
- Professor Giovanni Montana, University of Warwick – Advancing Multi-Agent Deep Reinforcement Learning for Sequential Decision Making in Real-World Applications
- Dr Christopher Nemeth, Lancaster University: Probabilistic Algorithms for Scalable and Computable Approaches to Learning (PASCAL)
- Dr Raul Santos-Rodriguez, University of Bristol – Interactive Annotations in AI
- Dr Sebastian Stein, University of Southampton – Citizen-Centric AI Systems
- Dr Ivan Tyukin, University of Leicester – Adaptive, Robust and Resilient AI Systems for the FuturE
- Dr Adrian Weller, University of Cambridge – Trustworthy Machine Learning
- Professor Christopher Yau, The University of Manchester – clinAIcan – Developing Clinical Applications of Artificial Intelligence for Cancer