Ariel Werle
Data Scientist
Rotterdam, South Holland, Netherlands
Summary
👤
Senior🎓
Top SchoolAriel Werle is a data scientist with a PhD in physics and 10 years of experience translating astrophysics research into production-ready machine learning solutions. After developing spectral classification CNNs and Bayesian inference workflows for galaxy studies at INAF—contributing to 30+ publications—he now applies similar algorithmic rigor to non-destructive testing of oil and gas pipelines at Pipesurvey International. He has strong hands-on experience with end-to-end scientific pipelines, hyperspectral data processing, and deploying ML models in applied engineering contexts. Based in Rotterdam, Ariel blends deep theoretical training with practical engineering, comfortable moving models from research code to integrated field systems. An understated strength is his track record of turning complex, noisy scientific data into robust, interpretable models that inform both discovery and operational decision-making.
9 years of coding experience
4 years of employment as a software developer
Doctor of Philosophy - PhD, Physics, Doctor of Philosophy - PhD, Physics at Universidade Federal de Santa Catarina
Stackoverflow
131reputation
89kreached
2answers
0questions
Github Skills (22)
spyder10
ide10
language-server-protocol10
anaconda10
pyqt10
qt9
python-development9
spectral9
python9
development-environment9
galaxy9
spectra8
starlight7
cloning6
synthesis6
Programming languages (2)
Github contributions (5)
arielwrl/starlight_toolkit
Jun 2017 - Jan 2021
A set of tools to manage the Starlight spectral synthesis code.
Contributions:72 commits, 2 PRs, 76 pushes in 3 years 7 months
spectralsynthesisstarlight
arielwrl/arielwrl.github.io
Jun 2020 - Mar 2024
Contributions:7 pushes, 1 branch in 3 years 8 months
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