My research lies at the intersection of computational mathematics and machine learning for applications to large-scale real world problems.
Keywords: Computational Mathematics 
Publications
GraphXCOVID: Explainable deep graph diffusion pseudo-Labelling for identifying COVID-19 on chest X-rays.
– Pattern Recognit
(2022)
122,
108274
(DOI: 10.1016/j.patcog.2021.108274)
A Three-Stage Self-Training Framework for Semi-Supervised Semantic Segmentation
– IEEE Transactions on Image Processing
(2022)
31,
1805
(DOI: 10.1109/TIP.2022.3144036)
Machine Learning for Workflow Applications in Screening Mammography: Systematic Review and Meta-Analysis.
– Radiology
(2021)
302,
88
(DOI: 10.1148/radiol.2021210391)
Learning optical flow for fast MRI reconstruction
– Inverse Problems
(2021)
37,
095007
(DOI: 10.1088/1361-6420/ac164a)
Dynamic spectral residual superpixels
– Pattern Recognition
(2021)
112,
107705
(DOI: 10.1016/j.patcog.2020.107705)
Compressed sensing plus motion (CS plus M): A new perspective for improving undersampled MR image reconstruction
– Medical Image Analysis
(2021)
68,
101933
(DOI: 10.1016/j.media.2020.101933)
Rethinking medical image reconstruction via shape prior, going deeper and faster: Deep joint indirect registration and reconstruction
– Med Image Anal
(2021)
68,
101930
(DOI: 10.1016/j.media.2020.101930)
Variational multi-task MRI reconstruction: Joint reconstruction, registration and super-resolution.
– Med Image Anal
(2020)
68,
101941
(DOI: 10.1016/j.media.2020.101941)
The GraphNet Zoo: An All-in-One Graph Based Deep Semi-supervised Framework for Medical Image Classification
– Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
(2020)
12443 LNCS,
187
(DOI: 10.1007/978-3-030-60365-6_18)
Superpixel Contracted Graph-Based Learning for Hyperspectral Image Classification
– IEEE Transactions on Geoscience and Remote Sensing
(2020)
58,
4180
(DOI: 10.1109/tgrs.2019.2961599)
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