Draga Pop
Napari Operations Manager
Melbourne, Victoria, Australia
Summary
🤩
Rockstar🎓
Top SchoolDraga Pop is a software engineer and PhD candidate in Data Science & AI based in Melbourne, with a decade of experience building open-source scientific software and teaching computational topics. She contributes to napari and the PyData ecosystem—improving core sparse-array DOK functionality and adding robust indexing and tests—while leading operations and developer-in-residence efforts for the napari project. As a co-founder of the Image Cooperative and an advocate for open research, she blends hands-on backend development with community-facing roles that make scientific tooling more accessible. Her background includes industry contracting at Chan Zuckerberg Initiative and early careers in software consulting and education, giving her both production-grade engineering skills and a knack for explaining complex ideas. Unusually for an active researcher, she pairs rigorous academic work on interactive cell segmentation interfaces with regular contributions to widely used open-source libraries.
10 years of coding experience
9 years of employment as a software developer
Bachelor of Information Technology, Information Technology, Bachelor of Information Technology, Information Technology at James Cook UniversityBachelor of Computer Science Advanced (Honours), Computer Science, Bachelor of Computer Science Advanced (Honours), Computer Science at Monash University
Github Skills (9)
image-segmentation10
visualization10
segmentation10
visualizations10
pytest10
python10
numpy10
testing9
user-interface9
Programming languages (8)
Github contributions (5)
pydata/sparse
Mar 2021 - Mar 2021
Sparse multi-dimensional arrays for the PyData ecosystem
Role in this project:
Back-end Developer
Back-end DeveloperContributions:1 review, 6 commits, 6 PRs in 18 days
Contributions summary:Draga primarily contributed to the development of the `sparse` library, focusing on enhancing the functionality of the `DOK` (Dictionary of Keys) sparse array format. Their work involved implementing features like fancy indexing, slicing capabilities, and equality comparisons for `DOK` arrays. They also addressed and fixed existing issues related to the `DOK` format's getitem functionality, as well as added comprehensive unit tests to validate the new features.
multi-dimensionalpythonsparsekd-treepydata
DragaDoncila/napari
Feb 2020 - Feb 2025
napari: a fast, interactive, multi-dimensional image viewer for python
Contributions:8 PRs, 415 pushes, 107 branches in 5 years 1 month
multi-dimensionalpythonimageimage-viewerdimensional
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