Paul Wright
AI Infrastructure Engineer (Isambard-AI) at Bristol Centre for Supercomputing (BriCS)
Exeter, England, United Kingdom
Summary
🤩
Rockstar🎓
Top SchoolPaul Wright is an AI Infrastructure Engineer and PhD physicist with a decade of hands-on experience translating cutting-edge ML research into production systems for space science and industry. He has led interdisciplinary teams and accelerators—from NASA FDL projects and Stanford research to commercial ML deployments—building end-to-end pipelines, MLOps, and web applications for solar forecasting and computer vision. As founder of Wright AI he consults across academia and startups, curating ML projects and organizing community events that bridge domain science and machine learning. Known for applying physics-informed losses and super-resolution architectures to real instrument calibration problems, he combines deep technical fluency with practical delivery across cloud and containerized environments. Based in Exeter, he brings a rare blend of academic presentation experience and production-grade infrastructure work, often turning mission-scale datasets into operational ML services.
10 years of coding experience
7 years of employment as a software developer
Master of Physics (MPhys) Physics with Astrophysics, Master of Physics (MPhys) Physics with Astrophysics at University of SouthamptonYear Abroad Astronomy and Astrophysics, Year Abroad Astronomy and Astrophysics at Harvard UniversityDoctor of Philosophy - PhD Physics, Doctor of Philosophy - PhD Physics at University of Glasgow
Github Skills (63)
algorithm10
algorithms10
fundamentals10
python10
astronomy10
c-programming10
astropy10
solar10
coding10
data-structures10
sun10
science10
computer-science10
pointnet9
sorting-algorithms8
Programming languages (10)
Github contributions (5)
PaulJWright/ColourBlind
Aug 2017 - May 2020
A Collection of Colour-blind-friendly Colour Tables
Contributions:4 releases, 94 commits, 4 PRs in 2 years 9 months
blindcolour
PaulJWright/DeepEM
Nov 2018 - May 2021
Demonstrating a Deep Learning Approach for DEM Inversion
Contributions:1 release, 75 commits, 68 pushes in 2 years 6 months
deep-learning
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