Deep AI Research in Health and Life Sciences

Democratising Artificial Intelligence to benefit patients around the world.

  • Mon 15th Nov 2021

Artificial Intelligence (AI) and Machine Learning have enormous potential for positive impact across health and life sciences, from early detection of disease to improving cancer treatment. I will start by tackling questions such as “What is AI?” and “How can we use AI responsibly?”. I will then describe three deep research projects at Microsoft where we are exploring how AI can be used for good. I will do a deep-dive into how the University of Cambridge and Addenbrookes Hospital have developed, and are deploying, state-of-the-art machine learning to speed up radiotherapy cancer treatment using Microsoft Research’s Project InnerEye open-source software. Then discuss how machine learning is being used to build a map of the human immune system, including to support COVID-19 response. And finally, how natural language processing can be used to make sense of millions of medical research publications to help accelerate drug discovery. I hope this will provide deep insights into how research at Microsoft is helping to democratise AI and empower research institutes, hospitals, and life science organizations to ultimately benefit patients around the world.

Dr. Kenji Takeda, Director of Academic Health and AI Partnerships, Microsoft Research, Cambridge

Dr Kenji Takeda is Director of Academic Health and AI Partnerships at Microsoft Research, based in Cambridge, UK. He is working to empower researchers to develop and deploy human-centric AI and machine learning, particularly to transform healthcare by exploiting data in the cloud, empowering those at the frontline of healthcare, and moving towards precision medicine. This includes medical imaging with Project InnerEye and working with the global healthcare data research community.

He regularly advises funding agencies and research organisations on innovation and technology strategy, including the Engineering and Physical Sciences Research Council, Science and Technology Funding Council, Medical Research Council, Wellcome Trust and Health Data Research UK. He is a visiting industry fellow at the Alan Turing Institute and visiting fellow at the University of Southampton, UK.

He was previously global lead for Microsoft’s Azure for Research program, helping researchers take best advantage of cloud computing, including through data science, high-performance computing, and the internet of things.

He spent over 20 years in academia as Associate Professor of Aeronautics and has a passion for developing novel computational and system-wide approaches to tackle fundamental and applied problems in science, engineering, and healthcare. He has extensive experience in cloud computing, high performance and high productivity computing, and engineering (aeronautics and astronautics, aerodynamics, aeroacoustics, and flight simulation).

He has received numerous awards, including the inaugural Royal Academy of Engineering Innovation prize, Royal Aeronautical Society Silver Award, and the Royal Academy of Engineering/ExxonMobil Gold medal for excellence in university engineering learning and teaching.

He worked for many years as a freelance computer journalist with ZDNet, GameSpot, Computer Gaming World, and PC Pilot.

Attending lectures

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The lecture will be preceded by a short presentation from a CSAR PhD Award Winner.

SyncTwin: Treatment Effect Estimation with Longitudinal Outcomes

Zhaozhi Qian, Department of Applied Mathematic and Theoretical Physics

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