Stefan Schouten
Software Engineer at GRIP Facility
Amstelveen, North Holland, Netherlands
Summary
👤
Senior🎓
Top SchoolStefan Schouten is a pragmatic software engineer with 9 years of experience building maintainable back-end systems, primarily in PHP (Zend, Symfony), Java, .NET and occasional Rust. He prefers architecting and implementing complex server-side solutions while contributing thoughtfully to front-end design and user-focused product decisions. Stefan brings hands-on experience in healthcare digitalization from Tenzinger and contributes to open-source research tooling—improving LibKGE’s back-end, plugin support and evaluation robustness. A certified Professional Scrum Master (PSM1), he combines team-centered problem solving with a reflective, continuous-learning approach honed during his Software Engineering studies. Unusually for an engineer, he channels creativity from a musical background (trained at conservatory and active as a keyboardist), which informs his collaborative and iterative design style. Based in Amstelveen, he enjoys turning intricate requirements into reliable, user-friendly software that stands the test of maintenance.
9 years of coding experience
5 years of employment as a software developer
Bachelor of IT, Computer Software Engineering, Bachelor of IT, Computer Software Engineering at Hogeschool van AmsterdamConservatorium Pop - Toetsen, Conservatorium Pop - Toetsen at Hogeschool INHOLLAND
Dutch, English
Stackoverflow
349reputation
19kreached
2answers
25questions
Github Skills (16)
configuration-management10
pytorch10
graph-embedding10
knowledge-graph10
python10
algorithm9
algorithms9
testing8
safari6
amp-html6
css6
google-plus6
google-api6
php6
javascript6
Programming languages (4)
Github contributions (5)
uma-pi1/kge
Dec 2020 - Sep 2021
LibKGE - A knowledge graph embedding library for reproducible research
Role in this project:
Back-end Developer
Back-end DeveloperContributions:6 reviews, 9 commits, 5 PRs in 9 months
Contributions summary:Stefan primarily focused on enhancing the `kge` library, which is designed for knowledge graph embedding. Their contributions involved refactoring code, and adding plugin support for loading models and embedders from external sources. The user also implemented features to improve the evaluation process, including handling ties in entity ranking, and incorporated configuration options for tolerance levels, ensuring robust model evaluation. Further, the user fixed bugs in the code to improve the software's accuracy and maintainability.
knowledge-graphreproducible-research
sfschouten/sfschouten.github.io
May 2019 - Nov 2024
Contributions:27 pushes, 1 branch in 5 years 7 months
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