I am a Research Associate at KCL, interested in developing machine learning-based tools and pipelines that can be deployed in the clinic. I currently work on developing segmentation algorithms that are accurate, generalisable, and uncertainty-aware. Prior to KCL I did my PhD at UCL where I built tools to simulate MRI Physics, and worked at a startup building deep-learning models to analyse retinal images.
ProjectsNeurology - Stroke
Risk of COVID-19 among front-line health-care workers and the general community: a prospective cohort study
Nguyen, L.H., Drew, D.A., Graham, M.S., Joshi, A.D., Guo, C.G., Ma, W., Mehta, R.S., Warner, E.T., Sikavi, D.R., Lo, C.H. and Kwon, S., 2020. The Lancet Public Health.
Graham, M.S., Drobnjak, I. and Zhang, H., 2018. NeuroImage, 178, pp.668-676.
Quantitative assessment of the susceptibility artefact and its interaction with motion in diffusion MRI
Graham, M.S., Drobnjak, I., Jenkinson, M. and Zhang, H., 2017. PloS one, 12(10).
Realistic simulation of artefacts in diffusion MRI for validating post-processing correction techniques
Graham, M.S., Drobnjak, I. and Zhang, H., 2016. NeuroImage, 125, pp.1079-1094.