Prof. Dr. Julia Anne Schnabel
Director of Institute of Machine Learning in Biomedical Imaging"My research focus is on developing novel machine learning solutions for medical imaging applications, such as early detection and characterisation of disease, and prediction of treatment outcome."
"My research focus is on developing novel machine learning solutions for medical imaging applications, such as early detection and characterisation of disease, and prediction of treatment outcome."
Academic Career
Julia A. Schnabel is Director of the Institute of Machine Learning in Biomedical Imaging at Helmholtz Munich (Helmholtz Distinguished Professorship) and Professor of Computational Imaging and AI in Medicine at Technical University of Munich (TUM Liesel Beckmann Distinguished Professorship), with secondary appointment as Chair in Computational Imaging at King’s College London. She graduated in Computer Science (equiv. MSc) from Technical University of Berlin, Germany in 1993, and was awarded the PhD in Computer Science from University College London, UK in 1998. In 2007, she joined the University of Oxford, UK as Associate Professor in Engineering Science (Medical Imaging), where she became Full Professor of Engineering Science by Recognition of Distinction in 2014, before joining King’s College London as a new Chair in 2015, and Helmholtz Munich and TUM in 2021. Dr. Schnabel has been elected Fellow of IEEE (2021), Fellow of ELLIS (2019), and Fellow of the MICCAI Society (2018). She is an Associate Editor of the IEEE Transactions on Medical Imaging on whose steering board she serves since 2021, of IEEE Transactions of Pattern Analysis and Machine Intelligence, of Medical Image Analysis, and Executive/Founding Editor of MELBA, a free online open-access journal for machine learning in biomedical imaging. She currently serves as elected Technical Representative on IEEE EMBS AdCom, as voting member of the IEEE EMBS Technical Committee on Biomedical Imaging and Image Processing (BIIP), as Executive Secretary to the MICCAI board, and as member of ELLIS Health and ELLIS Munich.
Julia's research interests are in machine/deep learning, nonlinear motion modelling, multi-modality, dynamic and quantitative imaging with applications in cancer, cardiovascular diseases, and fetal health. Her focus is on correcting complex types of motion, such as sliding organs or fetal movements, as well as imaging artefacts. She also has an interest in early disease detection, characterisation and prediction of response to treatment, with the aim of rapid translation into clinical practice for patient stratification and improved treatment outcome.
Skills
machine/deep learningmedical image computingcomputational imaging
Professional Background
Director, Institute of Machine Learning in Biomedical Imaging, Helmholtz Munich
Professor for Computational Imaging and AI in Medicine, Technical University of Munich
Chair in Computational Imaging, King’s College London, UK (part-time from 2021) and Director, Centre for Doctoral Training in Smart Medical Imaging at King’s College London and Imperial College London (2015-20)
Professor of Engineering Science by Recognition of Distinction, University of Oxford, UK
Associate Professor in Engineering Science (Medical Imaging), University of Oxford, UK
Honors and Awards
Helmholtz Distinguished Professorship
Helmholtz Association and
2021TUM Liesel Beckmann Distinguished Professorship
Technical University of Munich, Germany
2021Fellow, Institute of Electrical and Electronics Engineers (IEEE)
“For contributions to medical image computing”
2021Fellow, European Laboratory
for Learning and Intelligent Systems (ELLIS) Society
2019Fellow, MICCAI Society
“For contributions to multiple areas of medical image computing, and for distinguished service to the MICCAI conference and Society”.
2018
Key Publications
See allFacts
Julia Schnabel is an active mentor and promoter for the next generation of imaging scientists, both in terms of training and outreach, such as directing a large International Medical Imaging Summer School (MISS) in Favignana, Sicily, the AFRICAI network for for Artificial Intelligence in Biomedical Imaging (africai.org), and she is bringing the MICCAI conference for the first time to the African continent in 2024 (Marrakech, Morocco). Julia is also a fervent supporter of making research more accessible and affordable, as a founder and executive editor of the free fully online open-access Journal of Machine Learning in Biomedical Imaging (melba-journal.org).
