Biography
Professor Alison Noble CBE FRS FREng FIET is the Technikos Professor of Biomedical Engineering in the Department of Engineering Science and a Professorial Fellow of St Hilda’s College at the University of Oxford. She is a former Director of the Oxford Institute of Biomedical Engineering and former Associate Head (Industry Partnerships and Innovation) of Oxford's Mathematical, Physical and Life Sciences (MPLS) Division.
Her research lies at the intersection of artificial intelligence, computer vision and clinical medicine. She is internationally recognised for pioneering work in medical imaging, particularly ultrasound imaging, machine learning, and human-AI collaboration in healthcare. Her research spans next-generation ultrasound technologies, multimodal imaging, data-driven healthcare innovation, and global health applications in partnership with researchers and clinicians in Africa and India.
Professor Noble has led several major research programmes. In 2016, she was awarded a European Research Council (ERC) Advanced Grant, PULSE (Perception Ultrasound by Learning Sonographer Experience), exploring how multi-modal machine learning can transform ultrasound imaging. In 2023, she received a UKRI Turing AI World-Leading Researcher Fellowship focused on human-AI collaboration and federated learning for global healthcare imaging partnerships.
Alongside her biomedical engineering research, Professor Noble has a strong interest in science and AI policy. She chaired the working group behind the Royal Society's 2024 report on Science and AI and is the MPLS Division Director of the Oxford-UBS Applied AI Centre, which advances the application of AI in the financial sector.
Her contributions to engineering and healthcare technologies have been recognised by national and international honours, including the Royal Society Gabor Medal, the BMVA Distinguished Researcher Award, the MICCAI Society Enduring Impact Award, and the International Federation of Medical and Biological Engineering's Laura Bassi Award. She is also a Senior Fellow of the Hong Kong Institute for Advanced Study and a Hans Fischer Senior Fellow at the TUM Institute for Advanced Study in Germany.
Professor Noble has held several leadership roles in the international engineering and research community. She served as President of the MICCAI Society, chaired the EPSRC Healthcare Technologies Strategic Advisory Team, served on the EPSRC Science, Engineering and Technology Board, and was a full member of the REF 2021 Engineering Subpanel. She is currently a Trustee of HDRUK, and Vice President and Foreign Secretary of the Royal Society.
Throughout her career, Professor Noble has combined academic excellence with innovation and entrepreneurship. She was co-founder, director, and senior consultant to Intelligent Ultrasound, a University of Oxford spin-out specialising in AI-enabled ultrasound technologies. The company became a division of Intelligent Ultrasound PLC and was subsequently sold to GE Healthcare in 2024.
Professor Noble was appointed an OBE in 2013 for services to science and engineering and a CBE in 2023 for services to engineering and biomedical imaging.
Professor Noble was recently featured in Oxford's Women in AI series, highlighting her leadership and contributions to AI research and innovation.
Professor Noble leads the Noble Group. Further information about her group can be found here.
Most Recent Publications
FedExIT - Missing Class-agnostic Semi-Supervised Federated Learning with Extreme Imbalance Tackling Scheme
FedExIT - Missing Class-agnostic Semi-Supervised Federated Learning with Extreme Imbalance Tackling Scheme
SchistoTrackNet: machine learning for diagnosis of schistosomiasis-associated periportal fibrosis from ultrasound images
SchistoTrackNet: machine learning for diagnosis of schistosomiasis-associated periportal fibrosis from ultrasound images
SchistoTrackVideoNet: multilabel deep learning-based classification of schistosomal periportal fibrosis from ultrasound video
SchistoTrackVideoNet: multilabel deep learning-based classification of schistosomal periportal fibrosis from ultrasound video
View-Guided Multi-Task Learning for Fetal Cardiac Segmentation and CHD Classification
View-Guided Multi-Task Learning for Fetal Cardiac Segmentation and CHD Classification
Orientation-Robust Latent Motion Trajectory Learning for Annotation-free Cardiac Phase Detection in Fetal Echocardiography
Orientation-Robust Latent Motion Trajectory Learning for Annotation-free Cardiac Phase Detection in Fetal Echocardiography
Research Interests
- Biomedical imaging and image analysis
- Machine learning applied to healthcare
- Ultrasound image analysis
- Human-AI collaboration
- Federated analysis
- Point-of-care ultrasound
- Global health technologies
Professor Noble's collaborators and research partners include:
- Nuffield Department of Women’s and Reproductive Health, University of Oxford
- Visual Geometry Group, University of Oxford
- OxSTaR (Oxford Simulation, Teaching and Research), University of Oxford
- Translational Health Science and Technology Institute (THSTI), Faridabad, India
- PRECISE Network supported by GCRF
Additionally, her group has research projects funded by the following major research centres:
- NIHR Oxford Biomedical Research Centre – Professor Noble is co-lead of the Imaging Theme.
- Hong Kong Centre for Cerebro-cardiovascular Health Engineering (COCHE) – Professor Noble is a co-director and theme lead.
Other
For more information about Professor Noble’s research see here.
Most Recent Publications
FedExIT - Missing Class-agnostic Semi-Supervised Federated Learning with Extreme Imbalance Tackling Scheme
FedExIT - Missing Class-agnostic Semi-Supervised Federated Learning with Extreme Imbalance Tackling Scheme
SchistoTrackNet: machine learning for diagnosis of schistosomiasis-associated periportal fibrosis from ultrasound images
SchistoTrackNet: machine learning for diagnosis of schistosomiasis-associated periportal fibrosis from ultrasound images
SchistoTrackVideoNet: multilabel deep learning-based classification of schistosomal periportal fibrosis from ultrasound video
SchistoTrackVideoNet: multilabel deep learning-based classification of schistosomal periportal fibrosis from ultrasound video
View-Guided Multi-Task Learning for Fetal Cardiac Segmentation and CHD Classification
View-Guided Multi-Task Learning for Fetal Cardiac Segmentation and CHD Classification
Orientation-Robust Latent Motion Trajectory Learning for Annotation-free Cardiac Phase Detection in Fetal Echocardiography
Orientation-Robust Latent Motion Trajectory Learning for Annotation-free Cardiac Phase Detection in Fetal Echocardiography
Other Roles
National and International Roles
International Society Leadership International Medical Image Computing and Computer Assisted Interventions (MICCAI) Society: Served for 10 years on MICCAI Society Board: Society President (2013-16).
National Academy/Institution Leadership and Trusteeships
Royal Society: Vice President & Foreign Secretary (2023-), Trustee (2022-).
Health Data Research UK: Trustee (2024-).
Institution of Engineering and Technology (IET): Trustee (2016-19), Vice President (2019).
The Oxford Trust (Trustee, 2015-current).
National Academy Committees
Royal Society
Council, 2022-, Member. International Committee, 2024-, Co-Chair. Science Policy Committee, 2021-26, Member. Science Industry and Translation Committee, 2025-, Deputy Chair.
Industry Fellowship Joint Panel, 2019-2023, Chair. Sectional Committee 4 (2018) and 0 (2019-20), Member. Newton International Fellowships Committee, 2014-19, Member. Research Grants Panel, 2009-12, Member.
Royal Academy of Engineering
Enterprise Committee, 2013-22, Founding Member. External Affairs Committee, 2013-15, Member.
Awards Committee, 2009-12, Member.
National Academy Science Policy Working Groups
Royal Society: AI in Science Working Group (Chair, 2022-24, policy report). Privacy Enhancing Technologies (PETs) Policy Working Group, Chair for two data policy reports (2019, 2023).
Royal Academy of Engineering, Engineering Biology Steering Group (policy report, 2019).
National Assessment Panels
REF2021, Sub-panel 12 (Engineering), 2018-22, Member.
National and International Prize Committees
Schmidt Science Fellowships Final Selection, 2022-current, Panel Member and Panel Chair (2026).
Blavatnik Awards for Young Scientists in the United Kingdom, 2020, Jury Member.
Queen Elizabeth Prize in Engineering, Search and Nominations Group, 2016-18, Member.
UKRI Committees and Panels
EPSRC: SETB, 2022-26, Member. Healthcare Technology Strategic Advisory Team, 2017-19, Chair; 2014-19, Member.
Medical Research Council: Translational Research Group (TRG), 2014-19, Member. Stratified Medicine Group, 2016-19, Member. Reports to TRG. Innovate UK/MRC Biomedical Catalyst MAC Panel, 2014-16, Member. Confidence in Concept Panel, 2012-14, Member.
National Panels and Advisories – Other
UK Government Department Advisor - UK AI for Science Strategy, Expert group member advising on development for AI strategy, 2025.
Office for National Statistics, Integrated Data Programme Advisory Group, Member, 2021-current.
Government Blackett Review Panel, Member, 2016-17.
Most Recent Publications
FedExIT - Missing Class-agnostic Semi-Supervised Federated Learning with Extreme Imbalance Tackling Scheme
FedExIT - Missing Class-agnostic Semi-Supervised Federated Learning with Extreme Imbalance Tackling Scheme
SchistoTrackNet: machine learning for diagnosis of schistosomiasis-associated periportal fibrosis from ultrasound images
SchistoTrackNet: machine learning for diagnosis of schistosomiasis-associated periportal fibrosis from ultrasound images
SchistoTrackVideoNet: multilabel deep learning-based classification of schistosomal periportal fibrosis from ultrasound video
SchistoTrackVideoNet: multilabel deep learning-based classification of schistosomal periportal fibrosis from ultrasound video
View-Guided Multi-Task Learning for Fetal Cardiac Segmentation and CHD Classification
View-Guided Multi-Task Learning for Fetal Cardiac Segmentation and CHD Classification
Orientation-Robust Latent Motion Trajectory Learning for Annotation-free Cardiac Phase Detection in Fetal Echocardiography
Orientation-Robust Latent Motion Trajectory Learning for Annotation-free Cardiac Phase Detection in Fetal Echocardiography
Awards and Prizes
Commander of the Order of the British Empire (CBE) for services to Engineering and Biomedical Imaging in the King’s Birthday Honours list (2023)
Officer of the Order of the British Empire (OBE) for services to Science and Engineering in the Queen’s Birthday Honours list (2013)
Fellow of the Royal Society (2017)
Fellow of the Royal Academy of Engineering (2008)
Fellow of the Institute of Engineering Technology (IET) (2000)
Honorary Fellow of the St Hugh’s College, Oxford (2017)
Honorary Fellow of the Oriel College, Oxford (2016)
Fellow of the European Laboratory for Learning and Intelligent Systems (2021)
Fellow of the Women’s Engineering Society (2013)
Fellow of the Medical Image Computing and Computer Assisted Intervention (MICCAI) Society (2012)
Distinguished Fellow of the British Machine Vision Association (2022)
Gabor Medal, Royal Society (2019)
MICCAI Society Enduring Impact Award (2019)
Laura Bassi Award, International Federation of Medical & Biological Engineering (2015)
Senior Fellow, Hong Kong Institute of Advanced Study, CityU, Hong Kong
Hans Fischer Senior Fellow, TUM Institute for Advanced Study, Germany.
Most Recent Publications
FedExIT - Missing Class-agnostic Semi-Supervised Federated Learning with Extreme Imbalance Tackling Scheme
FedExIT - Missing Class-agnostic Semi-Supervised Federated Learning with Extreme Imbalance Tackling Scheme
SchistoTrackNet: machine learning for diagnosis of schistosomiasis-associated periportal fibrosis from ultrasound images
SchistoTrackNet: machine learning for diagnosis of schistosomiasis-associated periportal fibrosis from ultrasound images
SchistoTrackVideoNet: multilabel deep learning-based classification of schistosomal periportal fibrosis from ultrasound video
SchistoTrackVideoNet: multilabel deep learning-based classification of schistosomal periportal fibrosis from ultrasound video
View-Guided Multi-Task Learning for Fetal Cardiac Segmentation and CHD Classification
View-Guided Multi-Task Learning for Fetal Cardiac Segmentation and CHD Classification
Orientation-Robust Latent Motion Trajectory Learning for Annotation-free Cardiac Phase Detection in Fetal Echocardiography
Orientation-Robust Latent Motion Trajectory Learning for Annotation-free Cardiac Phase Detection in Fetal Echocardiography
Enquiries from potential DPhil (PhD) students who have interests in any of my research areas are welcome, please complete this survey.
Please note that Professor Noble does not accept Masters by Research (MRes) students.
She is also unable to offer in-person or remote internships.
Most Recent Publications
FedExIT - Missing Class-agnostic Semi-Supervised Federated Learning with Extreme Imbalance Tackling Scheme
FedExIT - Missing Class-agnostic Semi-Supervised Federated Learning with Extreme Imbalance Tackling Scheme
SchistoTrackNet: machine learning for diagnosis of schistosomiasis-associated periportal fibrosis from ultrasound images
SchistoTrackNet: machine learning for diagnosis of schistosomiasis-associated periportal fibrosis from ultrasound images
SchistoTrackVideoNet: multilabel deep learning-based classification of schistosomal periportal fibrosis from ultrasound video
SchistoTrackVideoNet: multilabel deep learning-based classification of schistosomal periportal fibrosis from ultrasound video
View-Guided Multi-Task Learning for Fetal Cardiac Segmentation and CHD Classification
View-Guided Multi-Task Learning for Fetal Cardiac Segmentation and CHD Classification
Orientation-Robust Latent Motion Trajectory Learning for Annotation-free Cardiac Phase Detection in Fetal Echocardiography
Orientation-Robust Latent Motion Trajectory Learning for Annotation-free Cardiac Phase Detection in Fetal Echocardiography