Head of Group

• Carola-Bibiane Schönlieb

Research Team

• Ander Biguri: Tomographic reconstruction, particularly in CBCT.
• Anna Breger: Mathematical image processing in medical problems with diverse data types.
• Zhongying Deng: Machine learning for brain and mental health.
• Chaoyu Liu: Machine learning for PDE and image processing.
• Carlos Esteve-Yagüe: Partial differential equations, and inverse problems.
• Julian Gilbey: Partial differential equations, and inverse problems.
• Michael Roberts: Variational methods for image processing, machine learning for image analysis.
• Johannes Schwab: Machine-learning methods for modeling continuous structural heterogeneity in cryo-EM reconstruction.

Ph.D. Students

• Mary Chriselda Antony Oliver: Analysis of graph-based semi-supervised algorithms by calculus of variation and optimal transport.
• Sam Cheng: Implicit deep learning: PDEs, ODEs and beyond.
• Simon Carlson: PhD in the BloodCounts!
• Yanqi Cheng: Optimisation for inverse problem
• Willem Diepeveen: Manifold valued inverse problems, Cryo-EM imaging.
• Holly Houliston: Study baleen whales by high-resolution satellite imagery.
• Daniel Kreuter: PhD in the BloodCounts!
• Kelly Kokka (Joint with the Public Health Modelling group): Biomedical imaging, machine learning.
• Yangming Li: Diffusion model.
• Wallace Peaslee: Mathematics for art investigation and cultural heritage.
• Christina Runkel: Geometric Deep Learning.
• James Rowbottom: Machine learning for PDEs.
• Zakhar Shumaylov: Geometric and physics informed DL for inverse problems.
• Hong Ye Tan: Machine learning with structural guarantees.
• Lipei Zhang: Physics-informed unsupervised learning in healthcare.

Visitors

• Chu Chen (visiting PhD student from CityU): Solving Inverse Problems in Dynamical Systems for Biomedical Imaging, and Machine Learning for Tomographic Reconstruction.
• Ziqi Qin: Non-smooth optimization.
• Mohamed Mikhail Kennerly: Domain adaptation for adverse weather conditions and semi-supervised learning.
• Prof Simon Foucart: Mathematical Data Science (including Compressive Sensing) with a strong Approximation Theory influence.
• Yaofang Liu
• Honglei Brinkmann

Former Members

• Hong Ye Tan (PhD student; 10/2021-03/2025), Designing Provably Convergent Algorithms from the Geometry of Data (joint with S. Mukherjee, IIT Kharagpur and Billy Tang, University of Birmingham), Currently Assistant Professor at UCLA.
• Lihao Liu (PhD student; 10/2020-05/2024; Co-supervised with Dr Angelica I. Aviles-Rivero), Advancing 3D Segmentation: Deep Learning Techniques for Video and Medical Imaging, Currently at Amazon
• Yijun Yang: Analysis mammography images for breast cancer classification.
• Tobias Wolf: Inverse problem.
• Jiahao Huang: Medical image analysis.
• Jan Stanczuk (PhD student; 10/2019-12/2023), Topics in Deep Generative Modelling Mathematical and Computational Aspects of Diffusion Models and Generative Adversarial Networks, Currently at Aspect Capital.
• Nina Dekoninck Bruhin: Functional data analysis in medical imaging
• Samuel Tull: PhD in the BloodCounts!
• Georgios Batzolis (PhD student; 10/2020-05/2025), Towards Learning the Geometry of Data: From Diffusion Models to Riemannian Geometry, Currently Postdoc with Mark Girolami, University of Cambridge
• Thomas Buddenkotte (PhD student; 10/2017-03/2022), Fully Automated Segmentation of High Grade Serous Ovarian Cancer on Computed Tomography Images using Deep Learning
• Willem Diepeveen (PhD student; 10/2020-06/2024), Riemannian geometry for inverse problems in cryogenic electron microscopy, Currently Assistant professor at UCLA
• Ferdia Sherry: Bilevel optimisation.
• Angelica I. Aviles-Rivero: Inverse problems, medical imaging, computational analysis and machine learning.
• Kweku Abraham: Theoretical guarantees for machine learning, frequentist validity of Bayesian procedures, false discovery rates, and hidden Markov models.
• Chaoyan Huang (Visiting PhD student): Convergence of Plug-and-Play Methods for Inverse Problems.
• George Rafael Domenikos: Thermodynamics, statistical physics andcryogenics.
• Sören Dittmer: Inverse problems, clinical time-series data, and topology optimization.
• Jongmin Yu: Machine learning for brain and mental health.
• Lihao Liu (PhD student): Unsupervised Medical Image Segmentation and video analysis.
• Nicolas Boulle: Numerical analysis and deep learning.
• Rui Guo: Remotes sensing application in agriculture disaster.
• Fangliangzi Meng: Integration of radiomics and genomics, multiomics data analysis and machine learning.
• Maximilian Kiss (Visiting PhD student): CT reconstruction.
• Jim Denholm (visiting PostDoc from Lyzeum Ltd.): Computer vision methods to analyze histopathological image data to celiac disease.
• Jan Cross-Zamirski (PhD student; 10/2018-01/2023), Cross-Modality Profiling of High-Content Microscopy Images with Deep Learning.
• Zhenda Shen (2023, visiting student from CityU, co-supervision with Angelica I. Aviles-Rivero): Implicit Neural Representations.
• Ben Schreiber (PhD student; 10/2019-09/2023), A Deep Learning Approach to Automated Coeliac Disease Diagnosis (joint with E. Soilleux, Pathology, Cambridge), Currently at GSK
• Tamara Grossmann (PhD student; 10/2018-09/2023), Deep Learning Approaches for PDE-based Image Analysis and Beyond: From the Total Variation Flow to Medieval Paper Analysis, Currently at Medtronic
• Laurent Pin (2023): Graph Based Medical Image Segmentation.
• Andrey Bryutkin (2022 - 2023): Graph Transformers for PDEs.
• Xiaoyu Wang (2018 - 2023): Machine learning for cell tracking in light microscopy.
• Ziruo Cai (May 2022 - May 2023): Uncertainty quantification in medical imaging, optimization and machine learning.
• Junqi Tang (2020-2022): Optimization, deep learning, medical imaging.
• Aurelie Bugeau (Jan - May 2023): Image and video processing and analysis.
• Nicolas Papadakis (Jan - May 2023): Computer vision, computational photography, oceanography, medical imaging.
• Nadja Gruber (Jan - April 2023): Chan-Vese model on medical image segmentation.
• Jing Zou (2022 - 2023): Feature Based Image Registration.
• Jean Prost (Sept - Dec 2022): HVAE for Image Restoration.
• Simone Saitta (Sept - Dec 2022): Physics informed denoising and super-resolution of 4D flow MRI.
• Chao Li: Neuroimaging, multi-omics, computational neuroscience, machine learning & deep learning.
• Subhadip Mukherjee: Machine learning, inverse problems in imaging, optimization, signal processing.
• Malena Sabaté Landman: Inverse Problems, mathematical Imaging, numerical linear algebra, generative models, functional data analysis.
• Rashmi Murthy: Inverse problems, applied partial differential equations.
• Lisa Kreusser: Partial differential equations, data analysis, and mathematical formulations for machine learning.
• Tatiana Bubba: Computational inverse problems with applications to medical imaging and spent nuclear fuels imaging.
• Debmita Bandyopadhyay: Multi-sensor data analysis, forest species mapping, Alpine vegetation dynamics, statistical modelling, machine learning.
• Yury Korolev: (2019 - 2022, PostDoc) Inverse Problems, Variational Methods, Mathematical Imaging, Theoretical Machine Learning.
• Chaoyu Liu (Mar - Aug 2022, visiting student from PolyU): Tumor segmentation and recurrence prediction with deep learning and PDEs.
• Chun-Wun (Sam) Chen (May - Aug 2022, visiting student from CityU): Delving into Neural ODEs for Fast MRI Reconstruction.
• Mickael Assaraf (May - Aug 2022, visiting student): Automated Graph Data Augmentation.
• Simone Parisotto: (2019 - 2022, PostDoc): Mathematics for cultural heritage, inverse problems, anisotropic variational models and PDEs.
• Nils Wachsmuth (Sept - Dec 2021, visiting student, ETH)
• Stefano van Gogh (Sept - Dec 2021, visiting student, ETH): Leverage data-driven methods to regularise the tomographic reconstruction problem.
• Rihuan Ke (2018 - 2022, Post-Doc): Inverse problems in adaptive optics and postprocessing, image processing and numerical linear algebra.
• Marcello Carioni (2018 - 2022, Post-Doc):: Inverse problems, machine learning, calculus of variations.
• Tatiana Bubba (2018 - 2022, Post-Doc): computational inverse problems with applications to medical imaging and spent nuclear fuels imaging.
• Hankui Peng (2020 - 2022, Post-Doc): subspace clustering, constrained clustering, active learning, image recognition, text mining.
• Lei Zhu (2020 - 2021, Post-Doc): Computer vision, image and video processing, medical imaging, and deep learning.
• Derek Driggs (PhD student; 10/2017-04/2022, joint with H. Fawzi, DAMTP, Cambridge), Accelerated Optimisation Algorithms for Machine Learning and Image Processing, Currently at Citadel
• Ferdia Sherry (2017 - 2021, PhD student): Structure-preserving machine learning for inverse problems, Currently at Voleon.
• Jonathan Williams (2017 - 2021, PhD student, co-supervision with David Coomes and Tom Swinfield, Plant Sciences): Analysis of airborne imaging data.
• Philip Sellars (2017 - 2021, PhD student, co-supervision with Angelica I. Aviles-Rivero, Anita Faul, Alistair Forbes and David Coomes): Minimal Labels, Maximum Gain. Image Classification with Graph-Based Semi-Supervised Learning.
• Sebastian Lunz (2016 - 2021, PhD student, co-supervision with Clément Mouhot): Machine Learning in Inverse Problems - Learning Regularisation Functionals and Operator Corrections, Currently at G-Research.
• Christian Etmann (2019 - 2021, Post-Doc): Inverse problems, deep learning, medical imaging, adversarial examples.
• Julian Gilbey (2019 - 2021, Post-Doc): Optical character recognition (OCR) in distorted images.
• Jonas Latz (2019 - 2021, Post-Doc):: Inverse problems, uncertainty quantification.
• Kasia Targonska-Hadzibabic (2019 - 2021, Post-Doc): Mathematics for cultural heritage.
• Lisa-Maria Kreusser (2019 - 2021, Post-Doc): Mean-field equations, biological networks.
• Madeleine Kotzagiannidis (2019 - 2021, Post-Doc): Analysis & exploitation of geometric structure in data for problems in signal processing and machine learning.
• Hugo Blanc (May - Aug. 2021, visiting student, ENSTA Paris - Institut Polytechnique de Paris): Semi-Supervised Image Classification for Hyperspectral Data.
• Shujun Wang (May - Aug. 2021, visiting PhD student, The Chinese University of Hong Kong)
• Wei Tang (June - Aug. 2021, visiting student, City University of Hong Kong): A Hybrid Model for Vessel Skeleton Extraction.
• Ula Komorowska (July - Aug. 2021, summer student, University of Cambridge): Partial Differential Equations: Finite Elements vs. Deep Learning.
• Christina Runkel (Sept. 2020 - Mar. 2021, visiting master student, University of Siegen): Provable Machine Learning for Medical Image Reconstruction.
• Rob Tovey (2016 - 2020, PhD student, co-supervision with Paul Midgley and Rowan Leary, Material Sciences): Mathematical challenges in electron tomography. Currently at Monumo.
• Jingwei Liang (2017 - 2020, Post-Doc): Non-smooth optimisation, image processing and machine learning. Now Lecturer at Queen Mary University of London.
• Zhuqing Li (June - Sept. 2020, summer student, City University of Hong Kong)
• Olivia Hu (June - Aug. 2020, summer student, University of Cambridge)
• Jiyang Du (June - Aug. 2020, summer student, University of Cambridge)
• Matthew Thorpe: (2017 - 2020, Post-Doc) Now Lecturer at the University of Manchester.
• Stephan Hilb (Jan. - Mar. 2020, visiting from University of Stuttgart)
• Lihao Liu (Feb. - Mar. 2020, visiting from Chinese University of Hong Kong)
• Hanne Kekkonen (2017 - 2020, Post-Doc). Now at TU Delft.
• Erlend Skaldehaug Riis (2015 - 2019, PhD student): Optimisation. Thesis: Geometric numerical integration for optimisation. Now London Mathematical Society Early Career Fellow at the University of Edinburgh.
• Shuai Liu (Dec. 2018 - Dec. 2019, visiting from Xi'an Jiaotong University)
• Patricia Vitoria Carrera (Sept. - Dec. 2019, visiting PhD student, Universitat Pompeu Fabra)
• Lara Raad (Oct. - Dec. 2019, visiting from Universitat Pompeu Fabra)
• Sören Dittmer (Aug. - Oct. 2019, visiting from University of Bremen)
• Nathan Blanken (May - Oct. 2019, visiting PhD student, University of Twente)
• Lisa-Maria Kreusser (2015 - 2019, PhD student, co-supervision with Bertram Düring and Peter A. Markowich): Anisotropic nonlinear PDE models and dynamical systems in biology (joint with P. A.Markowich, KAUST), Currently Reader at the University of Bath
• Tao Wei (June - Sept. 2019, visiting from State University of New York at Buffalo)
• Yao Yuan (June - Sept. 2019, visiting from National University of Singapore)
• Zak Shumaylov (June - Sept. 2019, summer student)
• Kaixuan Wei (July - Sept. 2019, visiting from Beijing Institute of Technology)
• Ethan Redmond (July - Sept. 2019, summer intern)
• Leon Bungert (July - Sept. 2019, visiting PhD student, Friedrich-Alexander-Universität Erlangen-Nürnberg)
• Kevin Han Huang (Aug. - Sept. 2019, summer student)
• Veronica Corona (2015 - 2019, PhD student, co-supervision with Stefanie Reichelt and Kevin Brindle, CRUK CI): Crossing Modalities in Cancer Imaging: Improving Diagnostics by Linking Light Microscopy with PET/MRI Using Novel Mathematical Methods. Thesis: Variational Multi-Task Models for Image Analysis: Applications to Magnetic Resonance Imaging. Now at Tenoke.
• Noemie Debroux (2018 - 2019, Post-Doc). Now at Université Clermont Auvergne.
• Guy Gilboa (Aug. 2019, visiting from Technion Israel Institute of Technology)
• Jonathan Ang (July - Aug. 2019, summer student): Walking Deeper on Graphs: Learning Latent Representations Via DeepWalk Approach.
• Jianchao Zhang (June - Aug. 2019, visiting summer student, City University of Hongkong): Superpixels segmentation.
• Marianne de Vriendt (June - Aug. 2019, master student): Learning to Classify Medical Images with Minimal Supervision.
• Timothée Schmoderer (June - July 2019, visiting PhD student, INSA Rouen Normandie): Joint Hybrid Variational Models.
• Ozan Öktem (Sept. 2018 - July 2019, visiting from KTH Royal Institute of Technology)
• Lukas Lang (2017 - 2019, Post-Doc). Now external lecturer at TU Wien.
• Pan Liu (2017 - 2019, Post-Doc). Now at BioMind.
• Nicolas Papadakis (Sept. 2018 - May 2019, visiting from Institute de Mathématiques de Bordeaux)
• Aurelie Bugeau (Sept. 2018 - May 2019, visiting from Université de Bordeaux)
• Simone Parisotto (2014 - 2018, PhD student, co-supervision with Simon Masnou, University of Lyon): Anisotropy in image processing. Thesis: Anisotropic variational models and PDEs for inverse imaging problems. Now PostDoc.
• Samar M. Alsaleh (Jan. 2019, visiting PhD student, Department of Computer Science, The George Washington University, USA).
• Maureen van Eijnatten (Oct. 2018 - Jan. 2019, visiting from Centrum Wiskunde and Informatica)
• Christian Etmann (Sept. - Nov. 2018, visiting PhD student, Center for Industrial Mathematics, University of Bremen).
• Ramona Sasse (Aug. - Nov. 2018, visiting PhD student, University of Münster).
• Qingnan Fan (Aug. - Oct. 2018, visiting PhD student, Computer Science and Technology School of Shandong University, China).
• Ruoteng Li (Aug. - Oct. 2018, visiting PhD student, Department of Computer Science, National University of Singapore).
• Martin Benning (2012 - 2018, Post-Doc). Now Lecturer at Queen Mary University of London.
• Matthias Ehrhardt (2016 - 2018, Post-Doc). Now Prize Fellow at University of Bath.
• Caroline Zhu (July - August 2018, undergraduate student, University of Cambridge): Learning Regularisation for Optical Flow. Awarded Funding: Cambridge Summer Research in Mathematics Programme (SRIM, 2018).
• Elena Resmerita (July 2018, visiting from University of Klagenfurt, Austria).
• Jiulong Liu (June - Sept. 2018, Department of Mathematics, National University of Singapore).
• Rosa Kowalewski (2017/18, master student, University of Luebeck): Deep neural networks for image registration.
• Joana Grah (2014 - 2018, PhD student, co-supervision with Stefanie Reichelt, CRUK CI): Mathematical image analysis for cancer research applications + PostDoc on Machine learning and medical imaging. Thesis: Mathematical Imaging Tools in Cancer Research - From Mitosis Analysis to Sparse Regularisation. Now PostDoc at Graz University of Technology.
• Rob Hocking (2013 - 2017, PhD student): Image and video inpainting. Thesis: Shell-Based Geometric Image and Video Inpainting.
• Tamara Großmann (2017, master student, University of Münster): Superresolution for photoacoustic tomography.
• Sebastian Neumayer (2016/17, master student, University of Kaiserslautern): Indirect image matching for tomographic inversion under shape priors.
• Georg Maierhofer (2016, summer intern): Learning an optimal sampling pattern for MRI.
• Vladimir Vankov (2016, summer intern): Classification and Standardization of Ancient Pottery by Machine Learning and Geometric Analysis.
• Emile Okada (2016, summer intern): Building imaging devices: from hardware to software.
• Chris Irving (2016, summer intern): Building imaging devices: from hardware to software.
• Wuhyun Sohn (2016, summer intern): Seismic imaging.
• Torbjørn Ringholm (July - August 2016, visiting PhD student from NTNU, Norway).
• Antonin Chambolle (September 2015 - June 2016, visiting from CMAP, Ecole Polytechnique, France).
• Marie Foged Schmidt (DTU, Denmark, February - June 2016).
• Ping Zhong (January 2015 - January 2016, visiting scholar from National University of Defense Technology, Changsha City, China).
• Gaohang Yu (January 2015 - January 2016, visiting scholar from Gannan Normal University, China).
• Yoeri Boink (September - December 2015, visiting master student from University of Twente): Motion analysis.
• Sam Thomas (2015, intern): InSAR phase unwrapping.
• Verner Vlacic (2015, intern): Dynamic image regularisation.
• Juheon Lee (2012 - 2016, PhD student). Thesis: Mapping individual trees from airborne multi-sensor imagery. Now PostDoc at Stanford University.
• Xiaohao Cai (2014 - 2016, PostDoc). Now PostDoc at UCL.
• Tuomo Valkonen (2012 - 2016, PostDoc). Now Lecturer at University of Liverpool.
• Luca Calatroni (2012 - 2015, PhD student). Thesis: New PDE models for imaging problems and applications. Now PostDoc in MIDA group of the University of Genova.
• Jan Lellmann (2011 - 2015, PostDoc and Leverhulme Early Career Fellow). Now Professor at the University of Lübeck.
• Evangelos Papoutsellis (2011 - 2015, PhD student). Thesis: First-order gradient regularisation methods for image restoration: reconstruction of tomographic images with thin structures and denoising piecewise affine images. Now PostDoc with Maitine Bergonioux at University of Orleans.
• Marie Autume (2012 & 2015, visiting intern, ENS Cachan): Art restoration. Joint supervision with Spike Bucklow from the Hamilton-Kerr Institute and Stella Panayotova from the Fitzwilliam Museum, Cambridge.
• Veronica Corona (2014/2015, visiting master student from University of Delft): Multi-spectral characterisation of thalamic nuclei with ultra-high field MRI. Joint with Peter Nestor (German Center for Neurodegenerative Diseases (DZNE), Magdeburg).
• Kostas Papafitsoros (PhD student until 2014, then PostDoc until mid-2015): Higher-order regularity in imaging. Thesis: Novel higher order regularisation methods for image reconstruction. He now holds a Humboldt Fellowship and is working with Michael Hintermueller at the Weierstrass Institute for Applied Analysis and Stochastics, Berlin, Germany.
• Maria Hänel (2014, visiting PhD student, University of Bayreuth): Optimal placement of cameras.
• Goezde Sarikaya (2014, intern): Reconstruction of MRI data.
• Rob Tovey (2014, intern): Higher-order convex-concave regularization.
• Stefi Anita (2014): Segmentation for radiotherapy treatment planning. Joint project with VoxTox.
• Ziad Kobeissi (2014, intern): Generating artificial fingerprints. Joint project with Bertram Düring (Uni Sussex), Carsten Gottschlich (Uni Göttingen), Stephan Huckemann (Uni Göttingen).
• Hendrik Dirks (2013, visiting David-Crighton Fellow, Westfälische Wilhelms-Universität Münster): Imaging of intracellular flows. Joint project with Ray Goldstein from DAMTP.
• Joana Grah (2013 - 2014, visiting Master's student, University of Münster).
• Rien Lagerwerf (2014/2015, visiting Master's student, University of Twente): TGV-type inpainting for limited-angle tomography. Joint with Christoph Brune (University of Twente, Netherlands)