Stefan Peterson
QA Architect at Epiroc
Luleå, Sweden
Summary
👤
Senior🎓
Top SchoolStefan Peterson is a QA Architect and software engineer with 11 years' experience applying signal processing, algorithm design and robust testing to industrial software at companies including Epiroc, Mobilaris and Tieto. He blends deep expertise in functional decomposition and data structures with hands-on experience optimizing scientific code—contributing performance and correctness improvements (and tests) to SciPy’s moment function. Based in Luleå, Sweden, he has moved from vibration analysis and NB‑IoT algorithm development into shaping QA architecture and developer workflows for mining intelligence. Stefan pairs a methodical, data-driven engineering style with curiosity-driven side projects—he's a polyglot programmer enthusiastic about Haskell and Rust and even practices unicycling as a hobby. His background in applied physics (M.Eng.) and broad experience across testing, algorithms and production software make him effective at marrying research-grade numerics with industrial-grade reliability.
11 years of coding experience
10 years of employment as a software developer
Master of Engineering (M.Eng.), Applied physics - electronics engineering, Master of Engineering (M.Eng.), Applied physics - electronics engineering at Luleå tekniska universitet / Luleå University of TechnologyExchange student, Electrical and Electronics Engineering, Exchange student, Electrical and Electronics Engineering at Monash University
English, Czech, French, Swedish, Russian, Ukrainian
Github Skills (8)
algorithms10
scipy10
python10
scientific-computing10
numpy10
data-analysis9
mathematical-optimization9
testing8
Programming languages (6)
Github contributions (5)
scipy/scipy
Feb 2015 - Dec 2018
SciPy library main repository
Role in this project:
Data Scientist
Data ScientistContributions:7 commits, 3 PRs, 14 comments in 3 years 10 months
Contributions summary:Stefan significantly contributed to optimizing the `moment` function within the SciPy library. Their work involved refactoring the code to enhance computational efficiency, addressing performance bottlenecks, and correcting potential errors. They improved the accuracy and speed of moment calculations. The user also added test cases to ensure the correctness and reliability of the updated functionality.
scipypythonscientific-computing
sjpet/planfftw
Oct 2015 - Jan 2020
Contributions:3 releases, 20 pushes, 2 branches in 4 years 3 months
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