Prof Carola-Bibiane Schönlieb
Carola-Bibiane Schönlieb is Professor in Applied Mathematics at the Department of Applied Mathematics and Theoretical Physics (DAMTP), University of Cambridge. There, she is head of the Cambridge Image Analysis group, Director of the Cantab Capital Institute for Mathematics of Information, Co-Director of the EPSRC Centre for Mathematical and Statistical Analysis of Multimodal Clinical Imaging, and since 2011 a fellow of Jesus College Cambridge. Her current research interests focus on variational methods and partial differential equations for image analysis, image processing and inverse imaging problems. Her research has been acknowledged by scientific prizes, among them the LMS Whitehead Prize 2016, and by invitations to give plenary lectures at several renowned applied mathematics conference, among them the SIAM conference on Imaging Science in 2014, the SIAM conference on Partial Differential Equations in 2015, the IMA Conference on Challenges of Big Data in 2016, the SIAM annual meeting in 2017 and the Applied Inverse Problems Conference in 2019.
Carola graduated from the Institute for Mathematics, University of Salzburg (Austria) in 2004. From 2004 to 2005 she held a teaching position in Salzburg. She received her PhD degree from the University of Cambridge in 2009. After one year of postdoctoral activity at the University of Göttingen (Germany), she became a Lecturer in at DAMTP in 2010, promoted to Reader in 2015 and promoted to Professor in 2018.
In her research Carola is interested in the interaction of mathematical sciences and imaging. She studies non-smooth and possibly non-convex variational methods and nonlinear partial differential equations for image analysis and inverse imaging problems, among them image reconstruction and restoration, object segmentation, and dynamic image reconstruction and analysis such as fast flow imaging, object tracking and motion analysis in videos. Moreover, she works on computational methods for large-scale and high-dimensional problems appearing in, e.g. image classification and 3D and 4D imaging.
Within this context she is interested in both the rigorous theoretical and computational analysis of the problems considered as well as their practical implementation and their use for real-world applications.
Currently, her research focuses on customising variational image analysis and image reconstruction models to applications by learning their setup from real-world data training sets. To this end she investigates so-called bilevel optimisation techniques in which the solution is typically constrained to a non-smooth variational problem or a nonlinear PDE.
She has active interdisciplinary collaborations with clinicians, biologists and physicists on biomedical imaging topics, chemical engineers and plant scientists on image sensing, as well as collaborations with artists and art conservators on digital art restoration.
Prof Dinggang Shen
Dinggang Shen is Jeffrey Houpt Distinguished Investigator, and a Professor in the Department of Radiology and BRIC at UNC-Chapel Hill. Before joining UNC as an associate professor in April 2008, he was a tenure-track assistant professor in the University of Pennsylvania since July 2002, and a faculty member in Johns Hopkins University in 2001 and 2002.
Dr. Shen is on the Advisory Board of Physics in Medicine & Biology (PMB) and Cognitive Computation (Springer Neuroscience, USA), and also the Editorial Board of the Journal of Alzheimer’s Disease (2016-2017), Medical Image Analysis, IEEE Transactions on Biomedical Engineering, IEEE Journal of Biomedical and Health Informatics (J-BHI), Pattern Recognition, Computerized Medical Imaging and Graphics, International Journal of Image and Graphics, CMBBE: Imaging & Visualization, and Brain Informatics. He also has served as a reviewer for numerous international journals and conferences.
Dr. Shen has published >800 articles in journals and proceedings of international conferences. He is the recipient of the title of SJTU Top Ten Research Elite (1994), best paper awards (1993,2001,2003,2005,2007), and the most cited paper award (2007). He is Fellow of IEEE, and also Fellow of The American Institute for Medical and Biological Engineering (AIMBE).