Jake Vanderplas
Software Engineer at University of Washington
Oakland, California, United States
Summary
🤩
Rockstar🎓
Top SchoolJake Vanderplas is a software engineer and data-science tooling expert with 16 years of experience, currently working on Google Colab to streamline workflows for researchers and data scientists. He combines deep academic credentials (PhD in Astronomy & Astrophysics) with hands-on engineering, contributing to cornerstone Python projects like NumPy, SciPy, scikit-learn, JAX, matplotlib, and Jupyter. His open-source work spans core numerical performance, ML algorithms, documentation and reproducible notebook tooling—often touching subtle numerical and API-quality issues such as KD-tree stability, sparse-array ops, and JAX API cleanups. Based in Oakland, he also serves as a Senior Data Science Fellow at the University of Washington, bridging research and production software. Colleagues rely on him for pragmatic refactors that improve maintainability and numerical correctness across widely used scientific libraries.
16 years of coding experience
6 years of employment as a software developer
Doctor of Philosophy (PhD), Astronomy and Astrophysics, Doctor of Philosophy (PhD), Astronomy and Astrophysics at University of WashingtonBachelor of Science (BS), Physics, Bachelor of Science (BS), Physics at Calvin College
Stackoverflow
81,637reputation
5.3mreached
1,702answers
13questions
image
top-1%
pandas
top-1%
jit
top-5%
dataframe
top-5%
matplotlib
top-1%
boxplot
top-5%
Github Skills (103)
notebook10
sparse-array10
restructuredtext10
python10
testing10
ipython10
text-formatting10
exporter10
markdown10
scikit10
charts10
pandas10
sparse-matrix10
statistics10
rs10
Programming languages (21)
Github contributions (5)
astroML/astroML
Oct 2012 - Sep 2018
Machine learning, statistics, and data mining for astronomy and astrophysics
Role in this project:
Technical Writer & Documentation Specialist
Technical Writer & Documentation SpecialistContributions:223 commits, 15 PRs, 36 pushes in 5 years 11 months
Contributions summary:Jake's commits primarily focus on updates and improvements to the documentation of the astroML project. The contributions include cleaning up and updating code examples for web pages, reformatting documentation, adding chapter information, fixing formatting errors, and adding an image. The changes suggest an emphasis on improving the presentation and usability of the documentation for the project.
data-miningmachine-learningstatistics
jakevdp/sklearn_tutorial
Sep 2015 - Nov 2019
Materials for my scikit-learn tutorial
Role in this project:Data Scientist
Data ScientistContributions:8 commits, 3 PRs, 7 pushes in 4 years 2 months
Contributions summary:Jake's commits focus on updating and expanding the materials for a scikit-learn tutorial. The initial commit sets up the tutorial, and subsequent commits update the content and add a data layout visualization to a notebook. These changes involve updating existing notebooks, which suggests a focus on refining and expanding the tutorial's content for machine learning concepts and the scikit-learn library.
scikit-learn
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