Andrew Nelson
Research Scientist at ANSTO
Sydney, New South Wales, Australia
Summary
🤩
Rockstar🎓
Top SchoolAndrew Nelson is a research scientist and software-focused physicist with 13 years of experience based at ANSTO in Sydney, combining experimental neutron and X-ray reflectometry expertise with deep open-source contributions to scientific Python. He maintains parts of SciPy and has improved testing and robustness across flagship projects like NumPy and emcee, streamlining test infrastructure and removing fragile dependencies to boost cross-platform reliability. His backend work has extended SciPy’s numerical integration and optimization tools and brought differential-evolution fitting into lmfit, reflecting a knack for turning numerical methods into production-ready code. Trained with a PhD in Physical Chemistry from the University of Bristol, he operates at the intersection of applied science and reproducible computation, favoring practical fixes that uncover subtle edge cases in sampling and numerical routines.
13 years of coding experience
6 years of employment as a software developer
PhD, Physical Chemistry, PhD, Physical Chemistry at University of Bristol
Github Skills (17)
algorithm10
scipy10
numerical-integration10
python10
optimizers10
testing10
numpy10
mcmc10
optimisation10
optimization10
test-automation10
pytest9
mathematical9
modeling9
documentation9
Programming languages (14)
Github contributions (5)
scipy/scipy
Apr 2013 - Jan 2023
SciPy library main repository
Role in this project:
Back-end Developer
Back-end DeveloperContributions:523 reviews, 558 commits, 639 PRs in 9 years 10 months
Contributions summary:Andrew's contributions primarily involve adding and improving functionalities within the SciPy library, specifically focusing on numerical integration techniques and optimization algorithms. Their work includes adding new parameters and features to existing functions, such as `scipy.integrate.quadrature`, and implementing the initial commit of differential evolution code. These changes involve modifying existing files related to optimization, indicating a focus on backend development and algorithm implementation using Python.
scipypythonscientific-computing
numpy/numpy
Jun 2015 - Jan 2023
The fundamental package for scientific computing with Python.
Role in this project:QA Engineer / Test Automation Engineer
QA Engineer / Test Automation EngineerContributions:64 reviews, 12 commits, 61 PRs in 7 years 8 months
Contributions summary:Andrew's contributions primarily revolve around improving the testing infrastructure and test coverage of the NumPy library. They fixed test error messages in `np.isclose` tests. The user also added tests and modified existing tests, demonstrating a focus on ensuring the quality and reliability of NumPy's numerical functionalities. Additionally, they addressed test failures related to musllinux, indicating efforts to maintain cross-platform compatibility.
pythonscientific-computingnumpy
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