Eric Larson - Research Scientist at University of Washington

Eric Larson

Research Scientist at University of Washington

Ann Arbor, Michigan, United States

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Summary

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Eric Larson is a Research Scientist in Ann Arbor with 13 years of experience building and deploying open-source neuroscience tools for MEG/EEG data analysis. He blends deep domain expertise in auditory neuroscience (PhD/MS in Biomedical Engineering) with strong backend software engineering, regularly contributing bug fixes, performance improvements, and test infrastructure to major scientific Python projects such as NumPy, SciPy, scikit-learn, and Matplotlib. His open-source work shows a practical focus on stability and reproducibility—fixing media codec issues in pyglet, optimizing Cython in DIPY, and hardening neuroimaging IO and transforms in nibabel and nilearn. Known for improving test suites and CI across projects like codespell and qtpy, he brings QA-minded rigor to research software. Colleagues rely on him to turn complex experimental workflows into robust, maintainable code that scales from lab experiments to community libraries.

13 years of coding experience

BA, Mathematics, Physics, and Philosophy, BA, Mathematics, Physics, and Philosophy at Kalamazoo College

MS/PhD, Biomedical Engineering, MS/PhD, Biomedical Engineering at Boston University

Thai

Github Skills (95)

restructuredtext10

python10

dijkstra10

testing10

pyside10

automation10

gpu10

cython10

build-automation10

code-cleanup10

3d10

linting10

medical-imaging10

game-development10

visualizations10

Programming languages (22)

PowerShellC++CSSRustCHolyCMakefileTeX

Github contributions (5)

mne-tools/mne-python

Sep 2012 - Jan 2023

MNE: Magnetoencephalography (MEG) and Electroencephalography (EEG) in Python

Role in this project:

Back-end Developer & Test Automation Engineer

Contributions:40 releases, 2613 reviews, 4556 commits in 10 years 5 months

Contributions summary:Eric's primary focus was on improving the software's robustness and reliability. They made significant contributions to the test suite by addressing test-related issues and incorporating fixes. The user also made code changes to ensure the correct execution of existing code functions related to the core functionality of the software. They worked within the constraints of the project's framework to address and resolve issues.

visualizationneuroimagingneurosciencepythonstatistics

sphinx-gallery/sphinx-gallery

Feb 2016 - Jan 2023

Sphinx extension for automatic generation of an example gallery

Role in this project:

Back-end Developer & Technical Writer

Contributions:8 releases, 242 reviews, 182 commits in 6 years 11 months

Contributions summary:Eric primarily contributed to bug fixes, improvements, and documentation updates within the Sphinx-Gallery project. They addressed issues related to import handling, exception handling, Unicode encoding, and logging practices, demonstrating a focus on code stability and robustness. The user also made significant contributions to enhancing the code's documentation, which included adding and modifying RST comments and adding new functionality. Their work ensures more robust and user-friendly library features.

pythonsphinx-extensionsphinxgalleryautomatic-generation

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