PhD candidate, trainee MRI physicist, and AI enthusiast. I work at the intersection of medical imaging, haemodynamics, and machine learning — building tools and models to understand blood flow and to make MRI science more reproducible and useful.
- 🎓 PhD candidate researching haemodynamics using deep learning and graph convolutional approaches
- 🧪 Trainee Magnetic Resonance (MR) Physicist — clinical & research MRI with NHS Wales
- 💻 Primary languages & tools: Python (ML & imaging), Fortran, R, Emacs Lisp; Emacs and Gentoo Linux for my development environment
- 🔬 Interests: MRI physics, flow modelling, quality assurance for imaging, AI for biomedical problems, reproducible computational science
- 🌱 Values: social justice, open science; member of the Bahá’í community
- 🍞 Outside of work: I enjoy bread baking and tinkering with scientific software
- Deep learning models for blood-flow analysis (including graph convolutional neural networks)
- MRI analysis pipelines and QA tooling
- Small, well-tested scientific libraries and CLI tools to make research workflows reproducible
- Emacs tooling and scripts to improve developer productivity
If you’re interested in MRI, haemodynamics, or bringing physics and ML together for healthcare, we’ll have plenty to talk about.
- Combining physics-based insight with data-driven models to improve interpretation of medical imaging
- Focus on open, well-documented code and reproducible experiments
- Comfortable across research, clinical-research translation, and software engineering workflows
- Website & blog: https://abdrysdale.phd/
- GitHub: https://github.com/abdrysdale
Thanks for stopping by — feel free to explore my repos or open an issue/PR if you find something useful (or broken)!