Aureliana Barghini
Senior Scientific Software Engineer at B-Open
Rome, Lazio, Italy
Summary
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Rockstar🎓
Top SchoolAureliana Barghini is a Senior Scientific Software Engineer based in Rome with 8 years of professional experience building robust tools for Earth observation and remote sensing. She blends a strong mathematical background and a master's in satellite remote sensing technologies with hands-on engineering at B-Open, where she progressed from Remote Sensing and Algorithm Specialist to senior software roles. Her open-source contributions include substantive back-end work on the widely used xarray library—adding CF/Zarr time-handling options, refactoring chunking and read APIs, and improving tests and docs to streamline large-scale scientific data workflows. Comfortable across algorithm development and production-grade software, she focuses on reliability and reproducibility in geospatial data processing. Colleagues rely on her for translating complex domain requirements into maintainable code and clearer documentation. She brings a quiet mix of deep domain knowledge and practical engineering that often surfaces in behind-the-scenes improvements to developer ergonomics.
8 years of coding experience
Master degree in Satellite Remote Sensing Technologies, Master degree in Satellite Remote Sensing Technologies at University of Barilaurea specialistica, Mathematics, laurea specialistica, Mathematics at Università degli Studi di Roma Tre
Github Skills (8)
xray10
netcdf10
python10
back-end-development10
xa10
numpy9
dask9
zarr9
Programming languages (3)
Github contributions (5)
pydata/xarray
May 2020 - Jun 2021
N-D labeled arrays and datasets in Python
Role in this project:
Back-end Developer
Back-end DeveloperContributions:44 reviews, 24 commits, 29 PRs in 1 year 1 month
Contributions summary:Aureliana primarily contributed to the xarray library by implementing new features and addressing bug fixes. They added an optional `decode_timedelta` kwarg to several functions related to CF conventions and Zarr backends, enhancing the library's handling of time-related data. The user also refactored code related to chunking and read API, streamlining data loading processes. Furthermore, they added tests and corrected documentation, improving overall code quality and usability.
pythonnetcdfnumpydaskarrays
bopen/cfgrib
Nov 2020 - Sep 2021
A Python interface to map GRIB files to the NetCDF Common Data Model following the CF Convention using ecCodes
Contributions:1 PR, 47 pushes, 12 branches in 9 months
meteorologyeccodespythonfollowingnetcdf
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