Sylwester Arabas
Scientific Researcher at AGH University of Krakow
Krakow, Lesser Poland Voivodeship
Summary
👤
Senior🎓
Top SchoolSylwester Arabas is a PhD-trained computational physicist and scientific researcher with 17 years of experience applying numerical methods and software engineering to atmospheric and cloud physics. He combines a research-first mindset with pragmatic, technical-debt-averse engineering—advocating reproducibility, open software, and KISS principles across academic and applied projects. His career spans postdoctoral and research roles at institutions including University of Warsaw, UIUC, Jagiellonian and AGH, and includes interdisciplinary work that bridges particle-based microphysics, MPDATA numerics and quantitative finance. An active open-source contributor, he has improved pedagogical resources such as the widely used Kalman-and-Bayesian-Filters-in-Python notebooks and helps maintain cloud-focused research tooling (open-atmos/PyPartMC). Based in Krakow, he researches "clouds in the cloud," blending cloud physics expertise with modern, reproducible computational workflows.
17 years of coding experience
7 years of employment as a software developer
Doctor of Philosophy - PhD, Physics, Doctor of Philosophy - PhD, Physics at University of WarsawStaszic
Polish, English, Russian, French
Stackoverflow
11reputation
0reached
1answer
0questions
Github Skills (5)
jupyter-notebook10
kalman-filter10
documentation10
tex8
astronomy6
Programming languages (22)
Github contributions (5)
rlabbe/Kalman-and-Bayesian-Filters-in-Python
Jan 2018 - Jan 2018
Kalman Filter book using Jupyter Notebook. Focuses on building intuition and experience, not formal proofs. Includes Kalman filters,extended Kalman filters, unscented Kalman filters, particle filters, and more. All exercises include solutions.
Role in this project:
Technical Writer
Technical WriterContributions:12 commits, 3 PRs, 2 comments in 5 days
Contributions summary:Sylwester's commits primarily involve updates and revisions to the Jupyter Notebook files within the repository. These changes include correcting typos and refining text in the documentation, enhancing the clarity and accuracy of the content. Specifically, the user focused on improving the descriptions and explanations of the Kalman filter concepts, as well as ensuring the proper display of the equations. The edits reflect a focus on improving the readability and comprehension of the technical material.
pythonjupyter-notebookkalman-filtersfiltersnotebook
open-atmos/PyMPDATA-examples
May 2021 - Feb 2023
PyMPDATA usage examples reproducing results from literature and depicting how to use PyMPDATA in Python from Jupyter notebooks
Contributions:17 releases, 1 review, 257 commits in 1 year 9 months
pythonpypi-packagejupyter-notebookadvection-equationpde-solver
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