Tom Andersson
Senior Research Engineer at Google DeepMind
London, England, United States
Summary
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Senior🎓
Top SchoolTom Andersson is a Senior Research Engineer with nine years of experience building and deploying AI systems for environmental sciences, currently at Google DeepMind where he works on ML-driven weather forecasting and sustainability initiatives. He holds an MEng from Cambridge and has led award-winning projects at the British Antarctic Survey, including IceNet (Nature Communications) and work that earned the WMO Young Scientist of the Year recognition. His joint-first author role on GenCast (Nature) and a deployed tropical cyclone model in partnership with the U.S. National Hurricane Center demonstrate a rare track record of moving research into operational forecasting. Tom combines deep ML research—neural processes, active learning, sensor placement—with production engineering, open-source tooling (DeepSensor), and cross-disciplinary collaboration with universities and policy partners. He has experience winning grant funding, supervising graduate projects, and communicating science through media and policy forums, indicating strengths beyond pure technical delivery. Notably, his work has been both academically influential and practically adopted by national weather services.
9 years of coding experience
6 years of employment as a software developer
Master of Engineering - MEng Information & Computer Engineering, Master of Engineering - MEng Information & Computer Engineering at University of CambridgeBudmouth CollegeIsle of Portland Aldridge Community Academy (IPACA), Royal Manor Campus
Stackoverflow
1reputation
0reached
0answers
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Github Skills (153)
python10
deep-learning10
neural-network10
hyperparameter-tuning10
data-science10
reinforcement-learning10
data-versioning10
tensorflow10
machine-learning10
keras10
pandas9
ml9
arctic9
forecasts9
ai9
Programming languages (8)
Github contributions (5)
tom-andersson/icenet-paper
Jul 2021 - Aug 2022
Code associated with the paper 'Seasonal Arctic sea ice forecasting with probabilistic deep learning'
Contributions:1 release, 60 commits, 22 pushes in 1 year
forecastingdeep-learningarcticsea-icemachine-learning
alan-turing-institute/deepsensor
Jun 2023 - Mar 2025
A Python package for tackling diverse environmental prediction tasks with NPs.
Contributions:43 releases, 34 reviews, 55 PRs in 1 year 9 months
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