Halvard Serigstad
Business Analyst at Coop Norge
Nordre Follo, Viken, Norway
Summary
👤
Senior🎓
Top SchoolHalvard Serigstad is a business analyst with a decade of hands-on experience bridging scientific research and operational logistics, currently driving data-informed decisions at Coop Norge. Trained as an organic chemist (MSc, UiO) who developed intramolecular Diels–Alder methods in his master’s thesis, he brings rigorous experimental problem-solving to process optimization and analytics. His background ranges from tutoring NMR and programming to frontline warehouse leadership, giving him rare fluency in both laboratory precision and large-scale supply chain execution. As an open-source ML contributor, he improved Ferminet’s configurability for ab‑initio electronic structure work, demonstrating an ability to translate domain science into robust code changes. This mix of chemistry, practical operations, and machine-learning contributions makes him adept at turning complex, technical problems into actionable business solutions.
10 years of coding experience
Master's degree, Organic Chemistry, Master's degree, Organic Chemistry at Universitetet i Oslo (UiO)
Github Skills (7)
machine-learning10
jax10
python10
calc9
tensorflow9
ec9
configuration-management9
Programming languages (4)
Github contributions (5)
google-deepmind/ferminet
Feb 2021 - Sep 2022
An implementation of the Fermionic Neural Network for ab-initio electronic structure calculations
Role in this project:
ML Engineer
ML EngineerContributions:1 review, 5 commits, 4 PRs in 1 year 6 months
Contributions summary:Halvard contributed to the Ferminet project by addressing issues related to input shapes and configurations. They corrected documentation and ensured compatibility with different system dimensions (ndim), essential for ab-initio electronic structure calculations. The user also updated the codebase by incorporating unused configuration parameters and modifying the initialization of electron positions. These changes suggest they were focused on improving the model's functionality and flexibility.
ab-initioelectronic-structure-calculationscalculationselectronic-structureelectronic
halvarsu/ferminet
Feb 2021 - Apr 2024
An implementation of the Fermionic Neural Network for ab-initio electronic structure calculations
Contributions:13 pushes, 7 branches in 3 years 2 months
ab-initioelectronic-structure-calculationscalculationselectronic-structureelectronic
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