AI/ML & Biomedical Imaging in Disease
Bartek will talk about their recent research on new methodologies advancing the frontiers of AI/ML and computational imaging techniques (multimodal data registration, weekly supervised annotation, image quality enhancement, and explainable AI).

Bio: Bartek has established an independent research group that focuses on medical imaging and machine learning at Big Data Institute. He is proud to have initiated several new, multidisciplinary research projects that integrate imaging and non-imaging modalities, driving the development of innovative image analysis and machine learning algorithms. Notably, his research projects encompass both the theoretical foundations of AI/ML algorithms (such as image quality, image segmentation, or image registration), and applied AI/ML for longitudinal disease monitoring (using imaging, patient records, and Natural Language Processing), identification of disease therapeutic targets (using imaging & genetic data integration), and more recently, multimodal cancer imaging & radiogenomics.

Bartek graduated in Electrical Engineering from the AGH University of Science and Technology in Kraków (Poland) in 2009. He completed a PhD at the University of Central Lancashire (UK) in 2012.

Research- Bartek joined the Biomedical Image Analysis Laboratory at the University of Oxford and between 2012 and 2017, he worked as a post-doctoral research fellow at the Oxford Cancer Imaging Centre focusing on cancer image analysis. In 2013, he was awarded a prestigious Young Scientist Award by the Medical Image Computing and Computer Assisted Intervention Society. In 2015, he was elected to an EPA Cephalosporin Junior Research Fellow at Linacre College. In 2018, he was awarded Rutherford Fund Fellowship at Health Data Research UK at the Big Data Institute in Oxford, which extended in Senior Fellowship in Population Health (from 2021).

Teaching- Bartek was a retained lecturer in Engineering Science at Exeter College (2018-20). Currently, I serve as a stipendiary lecturer at St Peter’s College, and Lady Margaret Hall. Bartek provides also lectures/workshop on Artificial Intelligence and Machine Learning (AI/ML) for Healthcare, Biomedical Image Analysis, Medical Imaging for various departments across the university and the external parties.

Hybrid Option:
Please note that these meetings are closed meetings and only open to members of the University of Oxford. Please respect our speakers and do not share the link with anyone outside of the University. We highly encourage in-person attendance at these seminars since they are intended to foster greater connection amongst people working in Phenome throughout the University.

There is time for discussion over, tea, coffee and pastries after the talk.

Microsoft Teams meeting
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Date: 22 November 2023, 14:00 (Wednesday, 7th week, Michaelmas 2023)
Venue: Big Data Institute, Old Road Campus OX3 7LF
Venue Details: Seminar Room 0
Speaker: Dr Bartek Papiez (University of Oxford)
Organising department: Big Data Institute (NDPH)
Organisers: Sumeeta Maheshwari (University of Oxford), Aiden Doherty (University of Oxford)
Organiser contact email address:
Host: Dr Aiden Doherty (University of Oxford)
Part of: Digital Phenotying
Booking required?: Not required
Booking email:
Cost: free
Audience: Members of the University only
Editor: Sumeeta Maheshwari