Vlas Sokolov
Data Scientist
Munich, Bavaria, Germany
Summary
👤
Senior🎓
Top SchoolVlas Sokolov is a data scientist based in Munich with 11 years of experience bridging astrophysics research and applied data engineering. He holds a PhD in astrophysics from Ludwig-Maximilians Universität and has moved from doctoral research at the Max Planck Institute into industry roles as a data engineer and now data scientist at Solita. Vlas combines strong statistical and data-visualization skills with production-minded engineering, having contributed to matplotlib’s mplot3d module by implementing advanced 3D error bar functionality. His background in electrophysics and astronomy gives him a rigorous quantitative foundation and an eye for noisy, high-dimensional scientific data. Colleagues describe him as a tinkerer who turns complex analyses into clear visual stories and reliable pipelines.
11 years of coding experience
6 years of employment as a software developer
Bachelor of Science - BS, Electrophysics, Bachelor of Science - BS, Electrophysics at National Chiao Tung UniversityLudwig Maximilian University of MunichMaster of Science - MS, Astronomy and Astrophysics, Master of Science - MS, Astronomy and Astrophysics at National Tsing Hua UniversitySecondary education, Secondary education at Kyiv Natural Science Lyceum
English, Ukrainian, Russian, Chinese, German
Stackoverflow
3,853reputation
232kreached
46answers
10questions
scipy
top-5%
matplotlib
top-5%
statistics
top-5%
pandas
top-5%
python
top-5%
Github Skills (18)
data-visualizations10
python10
matplotlib10
data-visualisation10
plot10
numpy10
3d10
data-visualization10
plot3d10
scipy9
pandas9
statistics9
legend6
combinations6
astropy6
Programming languages (7)
Github contributions (5)
matplotlib/matplotlib
Jan 2017 - Jul 2020
matplotlib: plotting with Python
Role in this project:
Back-end Developer
Back-end DeveloperContributions:21 commits, 1 PR, 28 comments in 3 years 7 months
Contributions summary:Vlas primarily contributed to the `mplot3d` module, adding and modifying functionality related to 3D error bars. They implemented a `errorbar3d` method, adding features like caplines, upper/lower limits and extended formatting. The user focused on integrating this into existing 3D plotting capabilities, and refining errorbar visualization features.
pythondata-sciencegtkdata-visualizationplotting
vlas-sokolov/multicube
Mar 2016 - Mar 2018
Contributions:156 commits, 6 PRs, 125 pushes in 2 years
pythoncubesguessesspectral-cubesspectral
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