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Department of Applied Mathematics and Theoretical Physics

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

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 Trans Image Process
(2021)
30,
3555
Variational multi-task MRI reconstruction: Joint reconstruction, registration and super-resolution.
V Corona, AI Aviles-Rivero, N Debroux, CL Guyader, C-B Schönlieb
– Medical Image Analysis
(2020)
68,
101941
Variational regularisation for inverse problems with imperfect forward operators and general noise models.
L Bungert, M Burger, Y Korolev, C-B Schönlieb
– Inverse Problems
(2020)
36,
125014
Learning the Sampling Pattern for MRI
F Sherry, M Benning, JC De Los Reyes, MJ Graves, G Maierhofer, G Williams, C-B Schonlieb, MJ Ehrhardt
– IEEE transactions on medical imaging
(2020)
39,
4310
Higher-order total directional variation: Imaging applications
S Parisottoy, J Lellmannz, S Masnoux, CB Schönlieb
– SIAM Journal on Imaging Sciences
(2020)
13,
2063
Scanning electron diffraction tomography of strain
R Tovey, DN Johnstone, SM Collins, WRB Lionheart, PA Midgley, M Benning, C-B Schönlieb
– Inverse Problems
(2020)
37,
015003
Preface for the special issue 'Variational methods and effective algorithms for imaging and vision'
CB Schonlieb, M Hintermuller, S Arridge
– Inverse Problems
(2020)
36,
110401
Accelerating variance-reduced stochastic gradient methods
D Driggs, MJ Ehrhardt, CB Schönlieb
– Mathematical Programming
(2020)
1
IUNets: Learnable invertible up-and downsampling for large-scale inverse problems
C Etmann, R Ke, CB Schonlieb
– IEEE International Workshop on Machine Learning for Signal Processing, MLSP
(2020)
00,
1
Optical flow analysis reveals that Kinesin-mediated advection impacts the orientation of microtubules in theDrosophilaoocyte
M Drechsler, LF Lang, L Al-Khatib, H Dirks, M Burger, C-B Schönlieb, IM Palacios
– Mol Biol Cell
(2020)
31,
1246
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Research Groups

Cambridge Image Analysis
Cantab Capital Institute for the Mathematics of Information
Centre for Mathematical Imaging in Healthcare

Room

F0.06

Telephone

01223 764251