Emily Reif
PHD Student at Superlative
Seattle, Washington, United States
Summary
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Rockstar🎓
Top SchoolEmily Reif is a research scientist and PhD student at the University of Washington who blends 11 years of software engineering experience with human-centered ML research at Google DeepMind's People + AI Research team. She focuses on interpretability—using visualization and novel interfaces to probe pretraining data and evaluate LLMs through their generated outputs for diverse users from pathologists to artists. Emily has deep front-end expertise (notably contributing UI improvements to PAIR-code/lit, a widely used interpretability tool), and a track record of shipping production-grade tooling at scale. Her background in visual arts and long-standing interest in human-facing design inform pragmatic, exploratory interfaces that reveal why models behave the way they do.
11 years of coding experience
2 years of employment as a software developer
Doctor of Philosophy - PhD Computer Science, Doctor of Philosophy - PhD Computer Science at University of WashingtonBachelor of Science (B.Sc.) Computer Science Visual Arts, Bachelor of Science (B.Sc.) Computer Science Visual Arts at Brown UniversityHigh School, High School at Carolina Friends School
French, English
Stackoverflow
1reputation
0reached
0answers
0questions
Github Skills (14)
uid10
typescript10
javascript10
typescripts10
front-end-development10
ui-design10
typescript-types10
react9
css8
html8
visualizations7
machine-learning7
visualization7
natural-language-processing6
Programming languages (5)
Github contributions (5)
PAIR-code/lit
Oct 2020 - Mar 2021
The Learning Interpretability Tool: Interactively analyze ML models to understand their behavior in an extensible and framework agnostic interface.
Role in this project:
Front-end Developer
Front-end DeveloperContributions:13 reviews, 22 commits, 2 PRs in 5 months
Contributions summary:Emily primarily contributed to the front-end of the "lit" repository, focusing on UI updates and enhancements. They implemented layout configuration changes and modifications to the global settings UI. Furthermore, the user updated the data table component to improve rendering and address display issues. These changes demonstrate a focus on improving the user interface and overall user experience within the LIT application.
ml-modelspythoninterpretabilitydata-sciencedeep-learning
PAIR-code/depth-maps-art-and-illusions
Jun 2019 - Aug 2021
Contributions:45 commits, 38 PRs, 37 pushes in 2 years 2 months
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