Jeremy Mcgibbon
Senior Machine Learning Research Engineer at Allen Institute for AI (AI2)
Old Toronto, Ontario, Canada
Summary
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Senior🎓
Top SchoolJeremy Mcgibbon is a Senior Machine Learning Research Engineer with a PhD in Atmospheric Sciences and 11 years of experience applying ML to weather and climate systems. He has a track record of translating advanced research into practical models—most notably using neural networks to represent subgrid clouds and turbulence and cutting multi-day forecast error by over half in single-column tests. At AI2 and previously Vulcan, he blends deep learning engineering (Keras/TensorFlow, recurrent architectures) with domain expertise from observational validation and high-resolution simulation work. Based in Toronto, he writes and maintains Python atmospheric modeling code and has a background running models on supercomputers and handling messy observational datasets. Colleagues rely on him for bridging rigorous research, reproducible code, and operationally-relevant predictions.
11 years of coding experience
8 years of employment as a software developer
Doctor of Philosophy - PhD, Atmospheric Sciences and Meteorology, Doctor of Philosophy - PhD, Atmospheric Sciences and Meteorology at University of WashingtonHonors Bachelor of Science, Physics, 3.85 CGPA, Honors Bachelor of Science, Physics, 3.85 CGPA at University of Toronto
English, French
Stackoverflow
3,695reputation
422kreached
82answers
5questions
windows
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anaconda
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cmd
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matplotlib
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python
top-5%
Github Skills (130)
climate-model10
python10
deep-learning10
netcdf10
statistics10
dataclasses10
jax10
atmospheric-modelling10
data-science10
tensorflow10
sphere10
data-analysis10
pytorch10
machine-learning10
scikit-learn10
Programming languages (11)
Github contributions (5)
mcgibbon/python-examples
May 2015 - Oct 2016
Contributions:28 commits, 20 pushes, 1 branch in 1 year 5 months
atmos-python/atmos
Mar 2015 - Aug 2018
An atmospheric sciences library for Python
Contributions:262 commits, 6 PRs, 119 pushes in 3 years 5 months
python
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