The UKRI will contribute £7.1 million to the project, which will be combined with funding from industry partners and Imperial to create a Centre worth £20 million.
Students of computer science, mathematics, and engineering, as well as
clinicians trained as PhD fellows on the four-year PhD courses will be supervised by experts in both AI and healthcare.
Dr Faisal said: “This is a fantastic opportunity to unite two disciplines that first seemed at opposite ends of the academic spectrum. Students will learn, under supervision from healthcare and AI experts, to use AI in, for example, clinical trials and diagnosis of disease.
“Imperial consistently demonstrates its expertise in both healthcare and AI, often combining both to create innovative ways to help people. We are delighted that we can now train PhD students in both disciplines to develop new leaders in this emerging field.”
In collaboration with clinicians, technology companies and patient organisations, the CDT will focus on making healthcare provision more efficient and effective by increasing the productivity of nurses, and developing AI-based diagnostics and monitoring that can detect disease earlier and monitor health with more precision.
We are increasingly using AI in all aspects of life, and healthcare is one of the areas where AI has the most potential to transform society. Professor Nick Jennings Vice-Provost (Research and Enterprise)
For example, a team of Imperial, MIT and Philips Healthcare researchers, led by Dr Faisal, recently created a new machine learning system inspired by robot learning, the AI clinician, that could boost chance of survival for sepsis patients.
Dr Faisal said: “AI for healthcare exemplifies all the challenges that make AI and machine learning difficult problems.
"We provide state-of-the art training in AI and machine learning, and apply them here in meaningful ways.”
Professor Nick Jennings , Vice-Provost (Research and Enterprise) at Imperial, said: “We are increasingly using AI in all aspects of life, and healthcare is one of the areas where AI has the most potential to transform society. We are, therefore, delighted to be recognised for our leadership in AI-based healthcare technologies, and for the opportunity to pursue this ground-breaking research area further.”
CDT in safe and trusted Artificial IntelligenceDirector: Professor Michael Luck , King’s College London
Imperial lead: Professor Alessio Lomuscio , Department of Computing
This CDT will train scientists and engineers in model-based AI approaches
and their use in developing safe and trusted AI systems.
The Centre, led by King’s, will equip new researchers with the knowledge of implications of AI on wider society, for example how self-driving cars might reason about interactions with people and the actions they should take.
Professor Lomuscio said: “I am delighted to lead this CDT from Imperial’s side. As the role of AI in our lives grows, we will train a new generation of scientists to ensure safety grows with it.”
New leadersAs well as a research element, students trained through CDTs receive technical and transferable skills training.
The Centres also aim to provide a supportive and exciting environment for students, creating new working cultures, building relationships between teams in universities and forging lasting links with industry.
Business Secretary Greg Clark said: “Artificial intelligence has great potential to drive up productivity and enhance every industry throughout our economy, from more effective disease diagnosis to building smart homes. Today’s announcement is our modern Industrial Strategy in action, investing in skills and talent to drive high skilled jobs, growth and productivity across the UK.”
UKRI Chief Executive, Professor Sir Mark Walport , said: “To maintain its leadership in AI, the UK will need a new generation of researchers, business leaders and entrepreneurs equipped with new skills. Working with partners across academia and industry, the centres announced today will provide the foundations for these future leaders.” Photos and graphics subject to third party copyright used with permission or © Imperial College London.
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