Hello, I'm Shelly

I'm passionate about building world-class data analytics and visualization products to enhance user understanding and decision-making.

As a staff software engineer at Visa, I lead the development of Visa Chart Components (VCC), an open-source accessibility-focused design system for data visualizations, along with its related data products.

My expertise spans both the tech and journalism sectors. In tech, I previously worked as a software engineer at Splunk, a Cisco company, where I built interactive visual tools to help businesses explore and monitor large data infrastructures efficiently.

In journalism, I've served as a data visualization developer / graphics reporter at esteemed newsrooms, including The Wall Street Journal, The Associated Press, NBC, and The Texas Tribune. I collaborated with reporters and editors to tell data-driven, visual stories on various topics, such as U.S. national and local elections, high-profile companies in business, and the impact of COVID-19.

My research paper on how captions affect visualization reading has been presented at IEEE Visualization Conference 2022 .

My visualization work has won awards from the European Journalism Centre, The Society of American Business Editors and Writers, The Society for News Design and Texas Medical Association, among others.


M.S. Computer Science, Columbia University
M.S. Journalism, Columbia University

B.A. Political Science, Colorado College

San Francisco, CA

Research

  • How Do Captions Affect Visualization Reading?

    Authors: [ Hazel Zhu, Shelly Cheng ]*, Eugene Wu (*equal contribution)
    IEEE Vis VisComm 2022

    Abstract: Captions help readers better understand visualizations. However, if the visualization is intended to communicate specific features, should the caption be statistical, and focus on specific values, or perceptual, and focus on general patterns? Prior work has shown that when captions mention visually salient features, users tend to recall those features. Still, we lack explicit guidelines for how to compose the appropriate caption. Further, what if the author wishes to emphasize a less salient feature?

Software Engineering

Front-end: HTML, CSS, JavaScript, TypeScript, D3.js, React.js, Styled-components, Maplibre-gl.js
Back-end: Python, Node.js, Flask, Java, Javalin, Linux
Testing: React testing library, Jest, Enzyme, Postman


Data Visualization Stories

Data scraped with Selenium and BeautifulSoup, cleaned with Pandas and Regex in Python,

design in Illustrator, Sketch and InVision, and built with HTML, CSS, JavaScript, React.js, D3.js, Bootstrap, etc.


Infographics

Data analysis using Python

Visualizing using HTML, CSS, d3.js, QGIS, Illustrator and Ai2html



Using Illustrator for print newspapers