Daniel Chen
Digital Content Producer & Research Assistant at The University of British Columbia
Richmond, British Columbia, Canada
Summary
🤩
Rockstar🎓
Top SchoolDaniel Chen is a digital content producer and research assistant with 12 years of experience blending storytelling, UX design, and community-engaged research to amplify Chinese Canadian history and public-facing scholarship. Based in Richmond, BC and anchored at UBC, he develops multimedia exhibits, virtual programming, and social campaigns—designing visitor experiences that invite community contribution while operationalizing heritage merchandise and outreach. His background in UX design and data-driven projects (including contributing to a SciPy Pandas tutorial and technical writing for the Software Carpentry website) reflects a pragmatic mix of content strategy, user research, and technical literacy. Comfortable behind a camera, in a design sprint, or editing HTML, he brings both creative production skills and an evidence-based approach to public humanities projects.
12 years of coding experience
The University of British ColumbiaDiploma, UX Design, Diploma, UX Design at RED Academy
Chinese, English
Stackoverflow
350reputation
31kreached
10answers
4questions
Github Skills (20)
content-management-system10
python10
pandas10
data-preprocessing10
content-management10
html10
data-analysis10
data-visualizations9
data-visualisation9
jupyter-notebook9
data-visualization9
seaborn8
scikit-learn7
scikit7
merge6
Programming languages (19)
Github contributions (5)
chendaniely/scipy-2017-tutorial-pandas
Jun 2017 - Dec 2020
SciPy 2017 Pandas Tutorial
Role in this project:
Data Scientist
Data ScientistContributions:33 commits, 3 PRs, 30 pushes in 3 years 5 months
Contributions summary:Daniel's contributions involve creating a Python script (`test_installation.py`) and modifying an IPython notebook (`01-pandas_intro.ipynb`) related to a Pandas tutorial. The initial commit includes importing Pandas, Seaborn, and Scikit-learn libraries, indicating a focus on data analysis and visualization within the Pandas ecosystem. Subsequent commits likely involved implementing data manipulation and analysis techniques, potentially covering data loading, cleaning, and basic exploratory analysis. The "data assembly" and "missing" commits, based on file names, suggest the user is implementing data preprocessing and handling missing data steps in the data analysis pipeline.
pythondata-sciencejupyter-notebookmachine-learningjupyter-widget
swcarpentry/website
Feb 2016 - Oct 2016
Software Carpentry website
Role in this project:Technical Writer
Technical WriterContributions:9 commits, 4 PRs, 6 comments in 8 months
Contributions summary:Daniel primarily contributed to updating the website's content, specifically focusing on the "SWDCRetreat2015 - Round-table discussion" post. The commits involved significant modifications to the HTML content, including updating dates, adding links, correcting spelling errors, and restructuring the layout with HTML tags. The user also replaced some text elements to make the content easier to navigate.
liquidcarpentryjekyllsoftware-carpentry
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