Frank Sauerburger
AI Engineer Lead at Sauerburger IT
Freiburg im Breisgau, Baden-Württemberg, Germany
Summary
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Rockstar🎓
Top SchoolFrank Sauerburger is an AI engineering lead and physicist with a decade of experience building and scaling ML-driven products and research software from Freiburg, Germany. He combines academic rigor—PhD-level physics and postdoctoral work—with hands-on engineering, leading cross-functional teams at MDPI and maintaining a long-running consultancy through Sauerburger IT. Frank has practical expertise in productionizing models, test automation, and scientific software QA, including notable open-source contributions to matplotlib where he implemented image-comparison tests for plotting fidelity in PDF/PS outputs. His background at CERN and university research informs a methodical approach to complex data and geometry problems, while his early web-design and freelance work keep his delivery pragmatic and user-focused. Colleagues know him for translating deep technical concepts into robust, testable systems that bridge research and product needs.
10 years of coding experience
8 years of employment as a software developer
Doctoral degree (Dr. rer. nat.), Physics, Doctoral degree (Dr. rer. nat.), Physics at The University of FreiburgNorwegian University of Science and Technology
German, French, Norwegian, English
Stackoverflow
4,848reputation
1.9mreached
99answers
25questions
docker
top-5%
http
top-5%
wordpress
top-5%
Github Skills (21)
data-visualizations10
python10
matplotlib10
testing10
data-visualisation10
data-visualization10
docker9
wordpress9
http9
test-automation9
pdf8
eps7
ttl6
curl6
permission6
Programming languages (9)
Github contributions (5)
matplotlib/matplotlib
Nov 2019 - Jul 2021
matplotlib: plotting with Python
Role in this project:
QA Engineer / Test Automation Engineer
QA Engineer / Test Automation EngineerContributions:12 reviews, 14 commits, 10 PRs in 1 year 8 months
Contributions summary:Frank primarily contributes to testing within the matplotlib repository, focusing on verifying the correct behavior and geometry of different plot types, including histograms and text rendering in PDF and EPS outputs. They create and modify test cases to cover various scenarios, such as stacked histograms, kerning in PDF fonts (Type 3, Type 42) and ensuring correct font embedding in PS output. Their work involves comparing images to expected outputs, demonstrating their use of image comparison tests to validate visual aspects of the library's plots.
pythondata-sciencegtkdata-visualizationplotting
sauerburger/matplotlib
Nov 2019 - Jul 2022
matplotlib: plotting with Python
Contributions:50 pushes, 14 branches in 2 years 8 months
pythonmathematicamatplotlibplottingwolfram-language
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