Dr Shuo Zhou
School of Computer Science
Lecturer in Machine Learning
Deputy Head of AI Research Engineering
Member of the Machine Learning research group
shuo.zhou@sheffield.ac.uk
Regent Court (CS)
Full contact details
Dr Shuo Zhou
School of Computer Science
Regent Court (CS)
211 Portobello
Sheffield
S1 4DP
School of Computer Science
Regent Court (CS)
211 Portobello
Sheffield
S1 4DP
- Profile
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Please replace my current profile with the following text:
Shuo Zhou is a Lecturer in Machine Learning at the School of Computer Science, University of Sheffield, and a member of the Machine Learning research group. He received his PhD in computer science (machine learning) from the same institution and previously worked as a Research Software Engineer, Research Assistant, and later as an Academic Fellow in Machine Learning. He is also one of the organisers of the Meta-Learning for Multimodal Data Interest Group at the Alan Turing Institute.
His work focuses on robustness, interpretability, and automation in machine learning, with applications in biomedical data analysis, particularly in neuroimaging and protein modelling. He also develops open-source software to support reproducible and scalable research, and co-founded the open-source library PyKale, a multimodal AI library in the PyTorch ecosystem, developed and maintained in academia.
- Research interests
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- Interpretable Machine Learning
- Medical Image Analysis
- Statistical Learning Theory
- Publications
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Journal articles
- Interpretable Multimodal Learning for Cardiovascular Hemodynamics Assessment. IEEE Transactions on Medical Imaging, 1-1.
- Group-specific discriminant analysis enhances detection of sex differences in brain functional network lateralization. Gigascience, 14. View this article in WRRO
- Interpretable multimodal learning for tumor protein-metal binding: Progress, challenges, and perspectives. Methods, 242, 97-112.
- 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
- First-person video domain adaptation with multi-scene cross-site datasets and attention-based methods. IEEE Transactions on Circuits and Systems for Video Technology, 33(12), 7774-7788. View this article in WRRO
- Improving multi-site autism classification via site-dependence minimization and second-order functional connectivity. IEEE Transactions on Medical Imaging, 42(1), 55-65. 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. View this article in WRRO
- Direct ICA on data tensor via random matrix modeling. Signal Processing, 196. View this article in WRRO
- 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. View this article in WRRO
- Neuropsychiatric disease classification using functional connectomics - results of the connectomics in neuroImaging transfer learning challenge. Medical Image Analysis, 70. View this article in WRRO
- Sturm: Sparse Tubal-Regularized Multilinear Regression for fMRI, 256-264.
- Domain Independent SVM for Transfer Learning in Brain Decoding.
- Towards deployment-centric multimodal AI beyond vision and language. Nature Machine Intelligence.
Book chapters
- Foundation-Model-Boosted Multimodal Learning for fMRI-Based Neuropathic Pain Drug Response Prediction, Lecture Notes in Computer Science (pp. 238-248). Springer Nature Switzerland
- 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, Lecture Notes in Computer Science (pp. 265-273). Springer International Publishing
Conference proceedings
- Leveraging artificial intelligence for predicting placebo vs treatment response in painful diabetic neuropathy. DIABETOLOGIA, Vol. 67 (pp S444-S444)
- 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. View this article in WRRO
- 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. View this article in WRRO
- 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. View this article in WRRO
Preprints
- Enhancing Speech Emotion Recognition via Fine-Tuning Pre-Trained Models
and Hyper-Parameter Optimisation.
- Towards deployment-centric multimodal AI beyond vision and language, arXiv.
- Multimodal Latent Fusion of ECG Leads for Early Assessment of Pulmonary Hypertension, arXiv.
- Interpretable Multimodal Learning for Tumor Protein-Metal Binding: Progress, Challenges, and Perspectives, arXiv.
- Foundation-Model-Boosted Multimodal Learning for fMRI-based Neuropathic Pain Drug Response Prediction, arXiv.
- Group-specific discriminant analysis reveals statistically validated sex differences in lateralization of brain functional network, arXiv.
- Multimodal Variational Autoencoder for Low-cost Cardiac Hemodynamics Instability Detection, arXiv.
- MeDSLIP: Medical Dual-Stream Language-Image Pre-training with Pathology-Anatomy Semantic 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. View this article in WRRO
- Interpretable Multimodal Learning for Cardiovascular Hemodynamics Assessment. IEEE Transactions on Medical Imaging, 1-1.
- Grants
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- A Novel Artificial Intelligence Powered Neuroimaging Biomarker for Chronic Pain, EPRSC, 10/2023 - 03/2025, £445,540, as Co-PI
- Towards Turing 2.0, RCUK, 07/2022 - 01/2023, £2,000, as PI.