John Reid
Research Engineer at DeepMind
London, England, United Kingdom
Summary
👤
Senior🎓
Top SchoolJohn Reid is a research engineer with 13 years of experience bridging academia and industry, currently driving research at DeepMind after leading AutoML and document-understanding teams at Blue Prism. He combines deep learning, classical ML and Bayesian statistics to take novel models from concept to production, with a particular interest in hybrids that marry Bayesian rigour with neural representational power. His background spans systems biology and neuroimaging—where he supervised generative-model work at the Alan Turing Institute and applied Bayesian methods in the Gurdon Institute—giving him rare domain fluency across biotech, healthcare and financial services. A seasoned team lead and mentor, he has hands-on experience shipping ML products in commercial settings and publishing research in collaborative environments. Notably, his career began in high-performance middleware and quantitative engineering, which informs a pragmatic, performance-conscious approach to productionising complex models.
14 years of coding experience
21 years of employment as a software developer
Bachelor of Arts, Mathematics, Bachelor of Arts, Mathematics at University of Cambridge11 'O'-levels and 4 'A'-levels, 11 'O'-levels and 4 'A'-levels at King Edward's School Bath
Github Skills (139)
spatial-transcriptomics10
gene-expression10
streamlit10
clustering10
dimensionality-reduction10
rna-seq10
r-package10
generative-model10
r9
autoencoder9
variational-autoencoder9
statistics9
posters9
api9
developer-tools9
Programming languages (11)
Github contributions (5)
JohnReid/bioinf-utilities
Aug 2012 - Nov 2013
Contributions:36 commits in 1 year 3 months
JohnReid/HAIS
Aug 2018 - Mar 2020
Hamiltonian Annealed Importance Sampling (HAIS) in tensorflow
Contributions:66 commits, 42 pushes, 1 branch in 1 year 7 months
tensorflowdeep-learninggenerative-modelhamiltonian-monte-carlomcmc
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