I am a computer vision DPhil/PhD student in the Visual Geometry Group at the University of Oxford, supervised by Professor Andrew Zisserman and Dr. Timor Kadir.
I am particularly interested in the application of machine learning to real-world problems in healthcare. Recently I have been focused on building automated methods to detect and analyse spinal disease in medical scans with a particular focus on cancer as well as data-efficient learning via self-supervision. I'm proud to be funded by Cancer Research UK and am a member of AIMS CDT. My CV is available here.
Applying for a PhD? If you're thinking of applying for a PhD, and you have questions regarding Oxford/AIMS/VGG/Computer Vision research in general, please don't hesitate to get in contact even if you feel like your background isn't suitable (I definitely felt that way when I applied). I'll try to respond as soon as possible although it may take a day or two.
07/08/2022: I am attending Oxford Machine Learning Summer School (healthcare track).
25/07/2022: SpineNet's source code is now publicly available. See the repo here
16/06/2022: "Context-Aware Transformers For Spinal Cancer Detection and Radiological Grading" has been accepted to MICCAI 2022. Preprint Link
05/05/2022: New paper provisionally accepted to MICCAI 2022! More News Soon
03/05/2022: SpineNetV2 Technical Paper Released. See the preprint here
23/10/2021: "3D Spinal Column Segmentation with Single Plane 2D-Projected Annotations" accepted to MedNeurips 2021!
17/09/2021: Presented 'Self-Supervised Multi-Modal Alignment for Whole Body Medical Imaging' at MICCAI 2021. See the talk on youtube here and the project page.
16/08/2021: Released DICOMcat, an simple pip-installable, open-source tool for quickly viewing DICOM files in the terminal. View on Github.
14/07/2021: Our new paper, 'Self-Supervised Multi-Modal Alignment for Whole Body Medical Imaging' has been accepted to MICCAI 2021! See arXiv (code coming soon)
22/04/2021: SpineNet Version 2 is now live! This software takes clinical spinal MRI scans as input and performs automatic vertebrae detection and labelling as well as radiological grading for a range of spinal diseases with accuracy comparable to clinical radiologists. Have a look at the online demo here.
06/07/2020: Our paper, 'A Convolutional Approach to Vertebrae Detection and Labelling in Whole Spine MRI ' was accepted to MICCAI 2020! See the arxiv version here
28/04/2020: Some work by our collaboration on automated scoliosis detection has been covered on the Department of Engineering Science website here.
12/04/2020: I've redesigned my website
03/04/2020: The first paper of my PhD, "The Ladder Algorithm: Finding Repetitive Structures in Medical Images by Induction" has been published at ISBI 2020. Have a look on arxiv .
A quick post detailing how I made this new website.