Professor Carola Bibiane Schönlieb

Professor Schönlieb is Professor of Applied Mathematics at DAMTP and head of the Cambridge Image Analysis group (CIA). Moreover, she is the Director of the Cantab Capital Institute for the Mathematics of Information (CCIMI) and Director of the EPSRC Centre for Mathematical and Statistical Analysis of Multimodal Clinical Imaging (CMIH), a Fellow of Jesus College, Cambridge and co-Chair of the Cambridge Centre for Data Driven Discovery (C2D3). Currently I am also chairing the SIAM activity group on Imaging Sciences and the Applied Mathematics Committee of the European Mathematical Society (EMS).

Career

Positions:

since October 2018: Professor at DAMTP, University of Cambridge, UK.
October 2015 to September 2018: Reader at DAMTP, University of Cambridge, UK.
since October 2011: Fellow of Jesus College, Cambridge, UK.
September 2010 to September 2015: Lecturer at DAMTP, University of Cambridge, UK.
September 2009 to September 2010: Postdoc at NAM (Institute of Numerical and Applied Mathematics), Georg-August University Goettingen, Germany.
October 2008 to September 2009: Research Assistant at DAMTP, University of Cambridge.
October 2005 to October 2008: Research Assistant at the Faculty of Mathematics, University of Vienna, Austria.
September 2002 to June 2004: Research Assistant at the Department of Mathematics, University of Salzburg, Austria.

Education:

July 18, 2009: Admission to the degree Doctor of Philosophy, University of Cambridge (UK)
January 30, 2004: Master’s degree in Mathematics with Honors, University of Salzburg (Austria)

Honors and Awards:

2020: Wolfson Fellowship, Royal Society UK.
2019: Calderón Prize, Inverse Problems International Association.
2017: Philip Leverhulme Prize.
2016: Whitehead Prize, London Mathematical Society.
2013: EPSRC Science Photo Award, 1st Prize in the Category People.
2008: Mary Bradburn Award from the BFWG.
2004: Scholarship from the University of Salzburg (Austria) for exceptional achievements as a student
2002: Hans-Stegbuchner-Award from the Department of Mathematics, University of Salzburg (Austria).

Research

Professor Schönlieb's research interests focus on variational methods, partial differential equations and machine learning for image analysis, image processing and inverse imaging problems. 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.. More details the website of her research group, Cambridge Image Analysis (CIA).

Publications

Imaging With Equivariant Deep Learning: From unrolled network design to fully unsupervised learning

D Chen, M Davies, MJ Ehrhardt, CB Schonlieb, F Sherry, J Tachella

– IEEE Signal Processing Magazine

(2023)

40,

134

(doi: 10.1109/MSP.2022.3205430)

Unsupervised Image Restoration Using Partially Linear Denoisers.

R Ke, C-B Schonlieb

– IEEE transactions on pattern analysis and machine intelligence

(2022)

44,

(doi: 10.1109/tpami.2021.3070382)

Label-free prediction of cell painting from brightfield images

JO Cross-Zamirski, E Mouchet, G Williams, C-B Schönlieb, R Turkki, Y Wang

– Scientific reports

(2022)

12,

10001

(doi: 10.1038/s41598-022-12914-x)

Data harmonisation for information fusion in digital healthcare: A state-of-the-art systematic review, meta-analysis and future research directions.

Y Nan, JD Ser, S Walsh, C Schönlieb, M Roberts, I Selby, K Howard, J Owen, J Neville, J Guiot, B Ernst, A Pastor, A Alberich-Bayarri, MI Menzel, S Walsh, W Vos, N Flerin, J-P Charbonnier, E van Rikxoort, A Chatterjee, H Woodruff, P Lambin, L Cerdá-Alberich, L Martí-Bonmatí, F Herrera, G Yang

– Information Fusion

(2022)

82,

(doi: 10.1016/j.inffus.2022.01.001)

Task adapted reconstruction for inverse problems

J Adler, S Lunz, O Verdier, CB Schönlieb, O Öktem

– Inverse Problems

(2022)

38,

075006

(doi: 10.1088/1361-6420/ac28ec)

Improving “Fast Iterative Shrinkage-Thresholding Algorithm”: Faster, Smarter, and Greedier

J Liang, T Luo, CB Schonlieb

– SIAM Journal on Scientific Computing

(2022)

44,

A1069

(doi: 10.1137/21M1395685)

A Three-Stage Self-Training Framework for Semi-Supervised Semantic Segmentation.

R Ke, AI Aviles-Rivero, S Pandey, S Reddy, C-B Schonlieb

– IEEE Transactions on Image Processing

(2022)

31,

1805

(doi: 10.1109/TIP.2022.3144036)

AI-Based Reconstruction for Fast MRI—A Systematic Review and Meta-Analysis

Y Chen, CB Schonlieb, P Lio, T Leiner, PL Dragotti, G Wang, D Rueckert, D Firmin, G Yang

– Proceedings of the IEEE

(2022)

110,

224

(doi: 10.1109/jproc.2022.3141367)

On Biased Stochastic Gradient Estimation

D Driggs, J Liang, CB Schönlieb

– Journal of Machine Learning Research

(2022)

23,

TFPnP: Tuning-free Plug-and-Play Proximal Algorithms with Applications to Inverse Imaging Problems

K Wei, A Aviles-Rivero, J Liang, Y Fu, H Huang, CB Schonlieb

– Journal of Machine Learning Research

(2022)

23,

ARTN 1

(link to publication)

Department of Applied Mathematics and Theoretical Physics

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