Stephen Liu is a delivery-oriented engineering manager with 11 years of experience blending front-end development, data science, and GenAI program delivery across fintech and enterprise software. A UC Berkeley double major in Data Science and Economics, he has driven quantitative trading and automation initiatives at RBC and Workday before leading GenAI delivery and strategic projects at Scale AI. He contributes to prominent open-source data-visualization tooling—improving React-based UI components for Apache Superset and adding advanced ECharts features—demonstrating deep UI/UX and charting expertise. Comfortable translating analytical requirements into production-grade interfaces, he pairs product sensibility with hands-on coding and Ant Design/React fluency. Outside work he’s shown entrepreneurial and creative drive—organizing fundraising music projects and founding campus data science programs that partnered with Walmart, Snapchat, and Qualcomm.
Apache Superset is a Data Visualization and Data Exploration Platform
Role in this project:
Front-end Developer
Contributions:195 reviews, 188 commits, 179 PRs in 1 year 10 months
Contributions summary:Stephen's commits primarily involve the modification of front-end components within the Apache Superset project. They fixed issues related to data panel scrolling, UI updates in the explore feature, and various dashboard and chart UI glitches. The commits demonstrate expertise in React, as well as experience with Ant Design components, and CSS styling.
Contributions:33 reviews, 45 commits, 52 PRs in 6 months
Contributions summary:Stephen primarily focused on enhancing the user interface (UI) for the Apache Superset UI packages. Their contributions involved implementing and refining the Echarts Treemap chart, including adding features like tooltip improvements, x-filtering capabilities, and single selection, as well as addressing related bugs. They also added similar functionality to other ECharts based charts in the library, like the radar, gauge, and mixed timeseries charts. Furthermore, they refactored the TimeSeries chart by adding support for series values.
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