Gordon Stevenson is a machine learning engineer with 11 years of experience applying ML, signal processing and ultrasound physics to medical imaging and translational research. He has led large pre-clinical and clinical validation studies—overseeing a AUD $100K large-animal study and forging collaborations with groups at the University of Michigan—while shipping novel automated tools for 3D ultrasound perfusion and placental assessment. His DPhil work at Oxford produced patented mesh-warping visualization and award-winning, reproducible techniques that later attracted NIH funding for automated placental analysis. Now at Vexev, he blends academic rigor with product-focused ML development to move imaging methods from validation to deployable software. Notably, he pairs deep domain knowledge in fetal and neonatal imaging with practical engineering skills to deliver clinically relevant automation that improves patient assessment.
11 years of coding experience
7 years of employment as a software developer
DPhil, Biomedical Engineering, DPhil, Biomedical Engineering at University of Oxford
Advanced Higher, Physics; Computer Science & Maths with Statistics, Advanced Higher, Physics; Computer Science & Maths with Statistics at George Watson's College
BSc (Hons), Computer Science & Physiology (Neuroinformatics), BSc (Hons), Computer Science & Physiology (Neuroinformatics) at University of Glasgow
Contributions:2 releases, 16 commits, 12 pushes in 2 years 10 months
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Gordon Stevenson - Machine Learning Engineer at Vexev