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Faculty of Mathematics



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My research lies  at the intersection of computational mathematics and machine learning for applications to large-scale real world problems. My central research is to develop new data-driven algorithmic techniques that allow computers to gain high-level understanding from vast amounts of data, this, with the aim of aiding the decisions of users. These methods are based on mathematical modelling and machine learning methods.

Keywords: \bigstarApplied Mathematics \bigstar Computational Mathematics \bigstar Inverse problems \bigstar  Image Analysis  \bigstar Graph Learning \bigstar Machine Learning.



GraphXCOVID: Explainable deep graph diffusion pseudo-Labelling for identifying COVID-19 on chest X-rays
AI Aviles-Rivero, P Sellars, C-B Schönlieb, N Papadakis
– Pattern Recognition
Learning optical flow for fast MRI reconstruction
T Schmoderer, AI Aviles-Rivero, V Corona, N Debroux, CB Schönlieb
– Inverse Problems
Delving Into Deep Walkers: A Convergence Analysis of Random-Walk-Based Vertex Embeddings
D Kloepfer, AI Aviles-Rivero, D Heydecker
LaplaceNet: A Hybrid Graph-Energy Neural Network for Deep Semi-Supervised Classification
P Sellars, AI Aviles-Rivero, C-B Schönlieb
– IEEE Transactions on Neural Networks and Learning Systems 2022
Dynamic spectral residual superpixels
J Zhang, AI Aviles-Rivero, D Heydecker, X Zhuang, R Chan, CB Schönlieb
– Pattern Recognition
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
Rethinking medical image reconstruction via shape prior, going deeper and faster: Deep joint indirect registration and reconstruction.
J Liu, AI Aviles-Rivero, H Ji, C-B Schönlieb
– Med Image Anal
Compressed sensing plus motion (CS + M): A new perspective for improving undersampled MR image reconstruction
AI Aviles-Rivero, N Debroux, G Williams, MJ Graves, C-B Schönlieb
– CoRR
Contrastive Registration for Unsupervised Medical Image Segmentation
L Liu, AI Aviles-Rivero, C-B Schönlieb
The GraphNet Zoo: An All-in-One Graph Based Deep Semi-supervised Framework for Medical Image Classification
M de Vriendt, P Sellars, AI Aviles-Rivero
– Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
12443 LNCS,
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Research Groups

Cambridge Image Analysis
Centre for Mathematical Imaging in Healthcare
Statistical Laboratory




01223 760377