Alex聽Matthews
Staff Research Scientist at Google DeepMind
Greater Cambridge Area United Kingdom
Summary
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Rockstar馃帗
Top SchoolAlex Matthews is a Staff Research Scientist at DeepMind with a decade of experience advancing statistics and machine learning, grounded in a PhD from the University of Cambridge under Zoubin Ghahramani. He has progressed through research roles at DeepMind since 2018 and maintains active academic ties as a Distinguished Visitor at Cambridge鈥檚 Cavendish Laboratory. His work spans Gaussian process modelling and scalable ML tooling鈥攅videnced by contributions to the widely used GPflow library where he improved regression notebooks, profiling, and model usability. Prior roles include industry-facing research and productisation at an Oxford spin-out that led to patents and embedded C++ systems, reflecting both deep theoretical expertise and practical engineering. Alex balances high-impact research with hands-on software development and open-source contributions, and he shares his work publicly via Google Scholar and an active technical presence on Twitter.
10 years of coding experience
13 years of employment as a software developer
Doctor of Philosophy - PhD Machine Learning, Doctor of Philosophy - PhD Machine Learning at University of Cambridge
Github Skills (7)
machine-learning10
tensorflow10
python10
gpflow10
api8
apim8
api-design8
Programming languages (2)
Github contributions (5)
GPflow/GPflow
Jan 2016 - Aug 2018
Gaussian processes in TensorFlow
Role in this project:
Back-end Developer
Back-end DeveloperContributions:2 releases, 310 commits, 145 PRs in 2 years 7 months
Contributions summary:Alex primarily contributed to the implementation and porting of a regression notebook and related features within the GPflow library. Their work involved translating the notebook to native Python, adding profiling functionality, and naming free variables within the model. The changes indicate a focus on enhancing the library's usability and performance, particularly for Gaussian process regression tasks.
information-theorygpflowdeep-learningmachine-learningmarkov-chain-monte-carlo
alexggmatthews/tensorflow
Mar 2016 - Apr 2016
Contributions:1 PR, 22 pushes, 2 branches in 1 month
computationscalabledata-sciencemachine-learninggraphs
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