Dr Shuo Zhou
School of Computer Science
Academic Fellow in Machine Learning
Member of the Machine Learning research group
shuo.zhou@sheffield.ac.uk
+44 114 222 1904
+44 114 222 1904
Regent Court (DCS)
Full contact details
Dr Shuo Zhou
School of Computer Science
Regent Court (DCS)
211 Portobello
Sheffield
S1 4DP
School of Computer Science
Regent Court (DCS)
211 Portobello
Sheffield
S1 4DP
- Profile
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Shuo Zhou is an Academic Fellow in Machine Learning at the University of Sheffield in the Machine Learning group, the Department of Computer Science. His work is now focused on developing interpretable machine learning methods and tools for analysing medical images / neuroimaging data.
Shuo Zhou completed his MSc in Advanced Computer Science (2017) and PhD (2022) in machine learning at the University of Sheffield. He is also a core developer of open-source library PyKale (https://github.com/pykale/pykale).
- Research interests
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- Interpretable Machine Learning
- Medical Image Analysis
- Statistical Learning Theory
- Publications
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Journal articles
- Tensor-based multimodal learning for prediction of pulmonary arterial wedge pressure from cardiac MRI. Medical Image Computing and Computer Assisted Intervention – MICCAI 2023: 26th International Conference, Vancouver, October 8-12, 2023, Proceedings, 14226. View this article in WRRO
- Machine learning cardiac-MRI features predict mortality in newly diagnosed pulmonary arterial hypertension. European Heart Journal - Digital Health, 3(2), 265-275.
- Direct ICA on data tensor via random matrix modeling. Signal Processing, 196.
- A machine learning cardiac magnetic resonance approach to extract disease features and automate pulmonary arterial hypertension diagnosis. European Heart Journal - Cardiovascular Imaging, 22(2), 236-245.
- Neuropsychiatric disease classification using functional connectomics - results of the connectomics in neuroImaging transfer learning challenge. Medical Image Analysis, 70.
- Sturm: Sparse Tubal-Regularized Multilinear Regression for fMRI, 256-264.
- Domain Independent SVM for Transfer Learning in Brain Decoding.
- First-Person Video Domain Adaptation with Multi-Scene Cross-Site Datasets and Attention-Based Methods. IEEE Transactions on Circuits and Systems for Video Technology.
- Improving multi-site autism classification via site-dependence minimization and second-order functional connectivity. IEEE Transactions on Medical Imaging.
Chapters
- Multimodal Variational Autoencoder for Low-Cost Cardiac Hemodynamics Instability Detection, Lecture Notes in Computer Science (pp. 296-306). Springer Nature Switzerland
- Improving Whole-Brain Neural Decoding of fMRI with Domain Adaptation, Machine Learning in Medical Imaging (pp. 265-273). Springer International Publishing
Conference proceedings papers
- PyKale: Knowledge-aware machine learning from multiple sources in Python. CIKM '22: Proceedings of the 31st ACM International Conference on Information & Knowledge Management (pp 4274-4278). Atlanta GA USA, 17 October 2022 - 17 October 2022.
- Confidence-quantifying landmark localisation for cardiac MRI. Proceedings of the IEEE International Symposium on Biomedical Imaging (ISBI 2021) (pp 985-988). Virtual conference, 13 April 2021 - 13 April 2021.
- Side information dependence as a regularizer for analyzing human brain conditions across cognitive experiments. Proceedings of the AAAI Conference on Artificial Intelligence, Vol. 34(4) (pp 6957-6964). New York, USA, 7 February 2020 - 7 February 2020.
Preprints
- Group-specific discriminant analysis reveals statistically validated sex differences in lateralization of brain functional network.
- Multimodal Variational Autoencoder for Low-cost Cardiac Hemodynamics Instability Detection, arXiv.
- MeDSLIP: Medical Dual-Stream Language-Image Pre-training for Fine-grained Alignment, arXiv.
- Tensor-based Multimodal Learning for Prediction of Pulmonary Arterial Wedge Pressure from Cardiac MRI, arXiv.
- Neuropsychiatric Disease Classification Using Functional Connectomics -- Results of the Connectomics in NeuroImaging Transfer Learning Challenge, arXiv.
- PyKale: knowledge-aware machine learning from multiple sources in Python.
- Grants
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Current Grants
- Neuroimaging: A Novel Artificial Intelligence Powered Neuroimaging Biomarker for Chronic Pain, UKRI, 10/2023 - 04/2025, £556,926
Previous Grants
- Towards Turing 2.0, RCUK, 07/2022 - 01/2023, £2,000, as PI.