**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

**Research **

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

**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.

## Publications

Unsupervised Image Restoration Using Partially Linear Denoisers

– IEEE transactions on pattern analysis and machine intelligence

(2021)

PP,

1

(DOI: 10.1109/TPAMI.2021.3070382)

Learning to Segment Microscopy Images with Lazy Labels

– Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

(2021)

12535 LNCS,

411

(DOI: 10.1007/978-3-030-66415-2_27)

Multi-Task Deep Learning for Image Segmentation Using Recursive Approximation Tasks

– IEEE transactions on image processing : a publication of the IEEE Signal Processing Society

(2021)

30,

3555

(DOI: 10.1109/tip.2021.3062726)

Efficient Preconditioning for Time Fractional Diffusion Inverse Source Problems

– SIAM Journal on Matrix Analysis and Applications

(2020)

41,

1857

(DOI: 10.1137/20m1320304)

iUNets: Learnable Invertible Up- and Downsampling for Large-Scale Inverse Problems

– 2020 IEEE 30th International Workshop on Machine Learning for Signal Processing (MLSP)

(2020)

2020-September,

1

Reconstruction of the high resolution phase in a closed loop adaptive optics system

– SIAM Journal on Imaging Sciences

(2020)

13,

775

(DOI: 10.1137/19m1258426)