Keynote Speakers
Andrew King
Professor in Medical Image Analysis, School of Biomedical Engineering and Imaging Sciences at King’s College London (KCL)
Dr King received a PhD degree in Computer Science from Warwick University in 1997 under the supervision of Professor Roland Wilson. From 2001-2005 he worked as an Assistant Professor in the Computer Science department at Mekelle University in Northern Ethiopia. Since 2006 he has worked at King’s College London, focusing on image analysis and AI in medical imaging. His research focuses on a range of methods and applications but he has a particular interest in trustworthy AI and algorithmic fairness for medical image analysis.
Dr King received a PhD degree in Computer Science from Warwick University in 1997 under the supervision of Professor Roland Wilson. From 2001-2005 he worked as an Assistant Professor in the Computer Science department at Mekelle University in Northern Ethiopia. Since 2006 he has worked at King’s College London, focusing on image analysis and AI in medical imaging. His research focuses on a range of methods and applications but he has a particular interest in trustworthy AI and algorithmic fairness for medical image analysis.
Susan Astley Theodossiadis
Professor of Intelligent Medical Imaging, The University of Manchester
Sue’s work is focused on the development and evaluation of imaging biomarkers for breast cancer risk, and the science underpinning stratified screening. Her research encompasses a range of technologies both for breast density measurement and early detection of cancer. Projects include the use of AI to predict cancers and to assess breast cancer risk from standard and ultra-low-dose mammograms, assessment of breast cancer risk in Saudi Arabia, evaluation of the impact of computer aided detection on reader behaviour and performance, reader variability studies, and the use of contrast enhanced mammography for evaluation of breast lesions. Her work is collaborative within a multidisciplinary network of scientists and clinicians in the UK and overseas. Sue started out as an astronomer and cosmic ray physicist before developing an interest in computation and medical imaging.
Sue’s work is focused on the development and evaluation of imaging biomarkers for breast cancer risk, and the science underpinning stratified screening. Her research encompasses a range of technologies both for breast density measurement and early detection of cancer. Projects include the use of AI to predict cancers and to assess breast cancer risk from standard and ultra-low-dose mammograms, assessment of breast cancer risk in Saudi Arabia, evaluation of the impact of computer aided detection on reader behaviour and performance, reader variability studies, and the use of contrast enhanced mammography for evaluation of breast lesions. Her work is collaborative within a multidisciplinary network of scientists and clinicians in the UK and overseas. Sue started out as an astronomer and cosmic ray physicist before developing an interest in computation and medical imaging.