Ryan Mullins
Staff Software Engineer at Google DeepMind
Somerville, Massachusetts, United States
Summary
🤩
Rockstar🎓
Top SchoolRyan Mullins is a Staff Software Engineer with 11 years of experience designing visualizations, user experiences, and analytics for Human-AI systems across cybersecurity, planning, and problem-solving domains. Based in Somerville, MA, he has progressed from research roles at Penn State and Aptima to engineering and tech-lead positions on Google’s People + AI Research team and now DeepMind, bridging research and production-grade tooling. He contributes front-end expertise to notable open-source projects like PAIR’s LIT, improving interpretability UIs and data-table interactions that help practitioners inspect model behavior. Comfortable spanning full-stack UI work and human-centered research, he focuses on making complex ML systems understandable and actionable for analysts and decision-makers. An unusual strength is pairing geographic and tactile interface research with modern ML interpretability, giving him a distinct perspective on spatial and interactive analytics.
11 years of coding experience
15 years of employment as a software developer
Master's degree, Geography, Master's degree, Geography at Penn State University
Github Skills (18)
javascript10
typescript10
ui-design10
uid10
front-end-development10
typescript-types10
typescripts10
web-development10
visualization9
data-visualizations9
data-visualisation9
visualizations9
react9
data-visualization9
html8
Programming languages (5)
Github contributions (5)
PAIR-code/lit
Oct 2021 - Jan 2023
The Learning Interpretability Tool: Interactively analyze ML models to understand their behavior in an extensible and framework agnostic interface.
Role in this project:
Full-stack Developer
Full-stack DeveloperContributions:4 releases, 58 reviews, 160 commits in 1 year 3 months
Contributions summary:Ryan primarily contributed to the frontend of the "lit" project, focusing on the development and refinement of user interface elements. They were involved in bug fixes for the "lit-data-table" and "classification-module" elements, addressing issues related to sorting and display bugs within score bars. Furthermore, the user implemented enhancements related to the display of tabular data, ensuring that the UI correctly reflects the underlying data values. They also implemented additional theming and styling changes, as well as adding functionality to the UI elements, such as the ability to pin or show only generated data points in the data table.
ml-modelspythoninterpretabilitydata-sciencedeep-learning
RyanMullins/angular-hammer
Dec 2014 - Jun 2016
Hammer.js v2 support for AngularJS
Contributions:20 commits, 11 PRs, 33 pushes in 1 year 5 months
hammerangularjsangular
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