Welcome to my academic website!

I am a final year PhD student at University College London, specialising in Machine Learning for Neuroimaging. My research focuses on creating robust representations to enable the use of deep learning models in real-world open-domain settings. My PhD has focused on applying this goal to the task of stroke segmentation in clinical MRI/CT data, under the supervision of Prof. John Ashburner and Prof. Cathy J. Price.

Research Interests

• Domain generalisation
• Synthetic data
• Semi/unupervised learning
• Generative modelling
• Uncertainty estimation

My work aims to develop robust and generalisable machine learning models for medical image analysis, particularly in the context of brain pathology segmentation. This research has the potential to improve diagnosis and treatment planning in clinical settings.

Currently, I am working on my PhD thesis, which explores novel approaches to domain generalisation and synthetic data generation for 3D medical image segmentation. This includes developing convolutional attention models, implementing self-supervised learning techniques, and creating physically-constrained synthetic data frameworks to enhance the performance and reliability of deep learning models in real-world clinical scenarios.

Recent Publication

My latest work, “Synthetic Data for Robust Stroke Segmentation”, explores the use of synthetic data in improving stroke segmentation techniques. This pre-print is now available on arXiv.

Feel free to explore my publications and CV to learn more about my academic journey and research contributions.