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Cambridge Image Analysis

Christina Runkel

Career

2021-present: PhD student in Mathematics of Information, University of Cambridge, UK

2018-2021: M.Sc. in Computer Science, University of Siegen, Germany

2015-2018: B.Sc. in Computer Science, Baden-Württemberg Cooperative State University Mannheim, Germany

Research

Christina is a PhD student at the Cambridge Image Analysis Group within the Department of Applied Mathematics and Theoretical Physics. She is also a member of the Cantab Capital Institute for the Mathematics of Information. Her current research focusses on deep learning and (medical) image analysis.

Publications

Continuous Learned Primal Dual
C Runkel, A Biguri, C-B Schönlieb
(2024)
(link to publication)
Continuous U-Net: Faster, Greater and Noiseless
C-W Cheng, C Runkel, L Liu, RH Chan, C-B Schönlieb, AI Aviles-Rivero
(2023)
(link to publication)
Learning Posterior Distributions in Underdetermined Inverse Problems
C Runkel, M Moeller, CB Schönlieb, C Etmann
(2023)
14009 LNCS,
187
(doi: 10.1007/978-3-031-31975-4_15)
Multi-Modal Hypergraph Diffusion Network with Dual Prior for Alzheimer Classification
AI Aviles-Rivero, C Runkel, N Papadakis, Z Kourtzi, C-B Schönlieb
– MICCAI 2022
(2022)
(link to publication)
Depthwise Separable Convolutions Allow for Fast and Memory-Efficient Spectral Normalization
C Runkel, C Etmann, M Möller, C-B Schönlieb
(2021)
(link to publication)
Exploiting the Logits: Joint Sign Language Recognition and Spell-Correction
C Runkel, S Dorenkamp, H Bauermeister, M Moeller
– 2020 25th International Conference on Pattern Recognition (ICPR)
(2020)
00,
5246
(doi: 10.1109/icpr48806.2021.9412952)

Research Group

Cambridge Image Analysis

Email

cr661@damtp.cam.ac.uk

Room

F0.13

Telephone

01223 339877

Study at Cambridge

About the University

Research at Cambridge