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Faculty of Mathematics



Education and Career

11/18 - now: Postdoctoral Research Associate, DAMTP, University of Cambridge
08/15 - 07/18: PhD Student, The Chinese University of Hong Kong



I am a Research Associate at the Department of Applied Mathematics and Theoretical Physics, University of Cambridge. My research interests are machine learning, inverse problems, image processing and numerical linear algebra

My google scholar profile.


Selected Publications

R. Ke and C.B. Schönlieb. Unsupervised image restoration using partially linear denoisers. IEEE Trans. Pattern Anal. Mach. Intell., 2021. DOI: 10.1109/TPAMI.2021.3070382
R. Ke, A. Bugeau, N. Papadakis, M. Kirkland, P. Schuetz, and C.B. Schönlieb. Multitask deep learning for image segmentation using recursive approximation tasks. IEEE Trans. Image Process., 30:3555–3567, 2021.
R. Ke, R. Wagner, R. Ramlau, and R. Chan. Reconstruction of the high resolution phase in a closed loop adaptive optics system. SIAM J. Imaging Sci., 13(2):775–806, 2020.
R. Ke, M. Ng, and T. Wei. Efficient preconditioning for time fractional diffusion inverse source problems. SIAM J. Matrix Anal. Appl., 41(4):1857–1888, 2020.
J. Pan, R. Ke, M. Ng, and H. Sun. Preconditioning techniques for diagonal-times-Toeplitz matrices in fractional diffusion equations. SIAM J. Sci. Comput., 36(6): A2698–A2719, 2014.





Unsupervised Image Restoration Using Partially Linear Denoisers
R Ke, C-B Schonlieb
– IEEE transactions on pattern analysis and machine intelligence
Learning to Segment Microscopy Images with Lazy Labels
R Ke, A Bugeau, N Papadakis, P Schuetz, CB Schönlieb
– Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
12535 LNCS,
Multi-Task Deep Learning for Image Segmentation Using Recursive Approximation Tasks
R Ke, A Bugeau, N Papadakis, M Kirkland, P Schuetz, C-B Schonlieb
– IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Efficient Preconditioning for Time Fractional Diffusion Inverse Source Problems
R Ke, MK Ng, T Wei
– SIAM Journal on Matrix Analysis and Applications
iUNets: Learnable Invertible Up- and Downsampling for Large-Scale Inverse Problems
C Etmann, R Ke, CB Schonlieb
– 2020 IEEE 30th International Workshop on Machine Learning for Signal Processing (MLSP)
Reconstruction of the high resolution phase in a closed loop adaptive optics system
R Ke, R Wagner, R Ramlau, R Chan
– SIAM Journal on Imaging Sciences

Research Group

Cambridge Image Analysis




01223 337867