Alexander Cowen-rivers
Biosecurity Research Engineer at Google DeepMind
London, England, United Kingdom
Summary
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Rockstar🎓
Top SchoolAlexander Cowen-rivers is a biosecurity research engineer at DeepMind with nine years of machine learning experience spanning academic research, industry R&D, and applied product analytics. He contributed to AlphaFold3 and its translation to Isomorphic Labs, and now focuses on AI for biosecurity, combining deep representation learning and reinforcement learning expertise. Previously a machine learning research scientist at Huawei Noah, he worked on hyperparameter optimization (HEBO) and earned an Innovation Pioneer award alongside publications in top venues and a patent. Alexander holds an MSc (Distinction) from UCL and is pursuing a PhD in Machine Learning at TU Darmstadt, bringing a strong mathematical background from a BSc in Mathematical Sciences. Notably, his open-source work on HEBO demonstrates a practical bent for improving optimization tooling that bridges research and production.
8 years of coding experience
4 years of employment as a software developer
Technischen Universität DarmstadtBSc Mathematical Sciences, Mathematics with a minor in Computer Science, BSc Mathematical Sciences, Mathematics with a minor in Computer Science at University of BathUniversity College London
Stackoverflow
1reputation
0reached
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Github Skills (10)
hyperparameter-optimization10
machine-learning10
python10
scikit-learn9
scikit9
pytorch9
testing8
pytest8
github-ci4
githubaction-workflow4
Programming languages (3)
Github contributions (5)
huawei-noah/noah-research
Jan 2021 - Feb 2022
Noah Research
Role in this project:
ML Engineer
ML EngineerContributions:31 commits, 3 PRs, 37 pushes in 1 year
Contributions summary:Alexander primarily contributed to the HEBO (Hyperparameter Optimization) component within the Noah Research repository. Their commits focused on refactoring and updating the `hebo.py` optimizer, including renaming files and integrating Evolutionary Strategy (ES) options. The user also modified test files and the `sklearn_tuner.py` file, demonstrating engagement with the testing and integration aspects of the HEBO library. These changes indicate an active role in the development and enhancement of the optimization functionality.
noah
alexanderimanicowenrivers/Neural-Variational-Knowledge-Graphs
May 2018 - May 2019
Contributions:1139 commits, 957 pushes in 11 months
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