Genevieve Buckley
Research Software Engineer at WEHI (Walter and Eliza Hall Institute of Medical Research)
Melbourne, Victoria, Australia
Summary
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Rockstar🎓
Top SchoolGenevieve Buckley is a research software engineer in Melbourne with eight years’ experience applying data science and image analysis to biomedical research. She has deep expertise in Python-based scientific computing, contributing QA and test automation to scikit-image and array enhancements and bug fixes to Dask — work that improved robustness for large-scale image processing and parallel computation in life sciences. At Monash she led cryo-EM image analysis and supported high-performance workflows, and she later advanced research software at WEHI while bridging developer best practices with domain science. Comfortable in both hands-on coding and researcher-facing consulting, she also brings practical experience integrating supercomputing resources and version control into reproducible pipelines.
8 years of coding experience
7 years of employment as a software developer
Bachelor of Arts/Science (Honours), Physics, Bachelor of Arts/Science (Honours), Physics at Monash University
Stackoverflow
1reputation
0reached
0answers
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Github Skills (22)
visualization10
pytest10
qt10
python10
image-processing10
testing10
xray10
scikit-image10
numpy10
list-processing10
array-map10
parallel-computing10
dask10
xa10
computer-vision10
Programming languages (13)
Github contributions (5)
dask/dask
Feb 2019 - Aug 2023
Parallel computing with task scheduling
Role in this project:
Back-end Developer / Data Scientist
Back-end Developer / Data ScientistContributions:126 reviews, 60 PRs, 613 comments in 4 years 7 months
Contributions summary:Genevieve primarily contributed to the `dask/dask` repository by implementing and enhancing array-related functionalities. This includes fixing bugs related to `bincount` and introducing features to improve array creation functions. Their contributions also involved improving existing functions, such as making the 'minlength' keyword argument optional in `dask.array.bincount` and updating array-related methods. The user also addressed issues with high-level graph representations.
pythonschedulingparallelnumpydask
scikit-image/scikit-image
Jun 2018 - Oct 2020
Image processing in Python
Role in this project:QA Engineer / Test Automation Engineer
QA Engineer / Test Automation EngineerContributions:2 reviews, 11 commits, 12 PRs in 2 years 4 months
Contributions summary:Genevieve's contributions primarily focused on improving the robustness and reliability of the `scikit-image` project. They added and updated unit tests for several image processing functions, including thresholding methods and histogram calculations. Furthermore, the user ensured dask compatibility for certain image processing algorithms by adding relevant unit tests and making code adjustments to facilitate integration. This work demonstrates a clear focus on quality assurance and test-driven development within the image processing domain.
image-processingpythoncomputer-visionimage
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