Claire Tang is a data scientist with 11 years of experience who blends rigorous neuroscience research with practical software engineering to build data-driven products. With a PhD from UCSF, she discovered pitch-responsive regions of human auditory cortex by designing experiments and scaling analysis pipelines from raw neural signals to publication-ready results. She has applied those skills in industry roles at Samba TV and Waymo, translating large, noisy datasets into actionable insights and production-ready models. An active open-source contributor, Claire made substantial full-stack improvements to the popular Bokeh visualization library, including layout and hit-testing refinements and interactive widget work. Based in San Francisco, she brings a rare combination of experimental design intuition, statistical rigor, and hands-on coding experience across frontend and backend systems.
11 years of coding experience
5 years of employment as a software developer
B.S., Applied Mathematics, B.S., Applied Mathematics at Emory University
Doctor of Philosophy (PhD), Neuroscience, Doctor of Philosophy (PhD), Neuroscience at University of California, San Francisco
Interactive Data Visualization in the browser, from Python
Role in this project:
Full-stack Developer
Contributions:33 commits, 29 PRs, 63 pushes in 2 years 2 months
Contributions summary:Claire made significant contributions to the Bokeh library, focusing on both frontend and backend aspects. They added and improved features to the `bokeh.io` module, specifically `vform`, by addressing bugs related to layout management and child removal. Furthermore, the user implemented and tested widget functionality and interaction in the user guide. The user's work included refactoring and improving hit-testing capabilities within the Javascript code.
Contributions:52 commits, 2 PRs, 20 pushes in 3 years 6 months
journalvisualizesimilarityscientistvisualization
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