Following the wider skills and talent package announced by the UK government earlier this year, we are now pleased to announce the appointment of five new and highly talented Turing AI Fellows.
The Office for Artificial Intelligence, The Alan Turing Institute and UK Research and Innovation (UKRI) have worked together to successfully attract the Turing AI Fellows, some of the best research talent from around the world.
To continue attracting outstanding AI talent, a new call for the Turing AI Acceleration Fellowship is now open. In addition, details of the Turing AI World-Leading Researcher Fellowships have also been released and this call is now open. Together, both calls have received £37.5 million of investment to support a number of fellows over five years. Further information is available on UKRI's website.
The Turing AI Fellows, who have been appointed for five years, are drawn from a wide variety of disciplines and backgrounds and will be tackling research challenges ranging from sustainable aviation to AI for discovery in data intensive astrophysics. Full details are listed here, along with a brief general synopsis of the projects they will be working on at the Turing:
Neil Lawrence, University of Cambridge, Senior Turing AI Fellow
Neil will be focusing on machine learning systems design. He will work on the entire pipeline of AI system development, from data acquisition to decision making. He proposes an ecosystem that includes system monitoring for performance, interpretability and fairness. And he places these ideas in a wider context that also considers the availability, quality and ethics of data.
Neil has also recently been named DeepMind Professor of Machine Learning at the University of Cambridge and is a co-host of the podcast Talking Machines.
Tim Dodwell, University of Exeter, Turing AI Fellow
Tim’s work addresses the challenge of building a more sustainable aviation industry by spanning traditional academic disciplines. The aim of his fellowship is to develop novel AI methods which fuse high-performance mathematical simulations and traditional experimental data to build a virtual test pyramid. This will increase the confidence in making the ultimate engineering decision: “Is this plane safe to fly?”. The new methods will not only allow the aerospace industry to build faster, lighter, more sustainable aircraft for the future, but provide new applications across the high-value manufacturing sector and broader scientific communities.
Yarin Gal, University of Oxford, Turing AI Fellow
Yarin will work on democratising safe and robust AI. While already in use in industry and academia, major obstacles still stand in the way of deploying deep learning AI safely and responsibly. Yarin proposes to tackle these problems by building community challenges derived from real-world applications of AI in industry. With the community competing on these public challenges, new safe and robust AI tools will be developed for responsible use in industry.
Maria Liakata, University of Warwick, Turing AI Fellow
Maria’s work as a Turing AI Fellow utilises language data obtained from wide-spread use of digital technology such as social media as well as mobile phone data to develop novel natural language processing methods for automatically capturing changes in user behaviour over time. This work has direct applicability to mental health as it will help provide experts with evidence for personalised changes in mood and cognition from everyday use of digital technologies. Major outputs of this project are novel tools for personalised monitoring behaviour through language use and user generated content over time and the co-creation with clinical experts of new cost-effective tests to support monitoring and diagnosis.
Anna Scaife, University of Manchester, Turing AI Fellow
Anna’s Turing AI Fellowship focuses on AI for discovery in data intensive astrophysics. In this era of big data astrophysics, radio telescopes like the Square Kilometre Array (SKA) have data rates so large that the raw data cannot be stored, and even using the compressed data products requires a super-computer. Anna will develop new machine learning approaches to deal efficiently with these huge data volumes, and address the question of how we can still allow for discovery when such processing is completely automated. In particular, she will focus on how we can incorporate knowledge from historical data into the machine learning for new experiments like the SKA without introducing biases that adversely affect the results.
“AI has the potential to boost productivity and enhance every industry across the economy, from developing new treatments for life-threatening diseases to tackling climate change. Today’s announcement is helping us solve the UK’s Grand Challenges by ensuring the UK is at the forefront of the latest technologies and opening-up British businesses to new opportunities.
“The UK is a petri-dish for incredible talent and we’re passionate about nurturing the next generation of world-class scientists, so the UK remains at the forefront of research and innovation.
“That is why we’re investing in the AI and bioscience PhD research. These critical areas will transform the UK economy and create the highly-skilled workforce we need for the future.”
Digital Minister Matt Warman said:
“The UK has a long-standing reputation for innovation. We are the birthplace of artificial intelligence and home to technology pioneers such as Alan Turing and Ada Lovelace. We are determined to see this continue.
“Today we are announcing a bumper investment in skills training to strengthen our workforce and attract, nurture and retain the best talent so we can lead the world in research and development.
“AI is already being used to improve lives by helping detect fraud quicker and diagnose diseases more accurately. With the brightest minds at the helm we will be able to explore this cutting-edge technology further."
Adrian Smith, Institute Director and Chief Executive of The Alan Turing Institute, said,
“We look forward to what this talented group of Turing AI Fellows will bring to our vibrant research community and we welcome their contributions to our growing Institute. There is vast potential for their diverse work to be transformative in both the foundations and applications of AI and I am confident they will push the boundaries of what these new technologies can do for the good of society.”
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Note: This article was updated on 25 October 2019 to reflect the opening of the Turing AI Acceleration Fellowships call. It was also updated on 15 November 2019 to reflect the opening of the Turing AI World-Leading Researcher Fellowships.