Cynthia E Chen
Software Engineer
About Me
I am a software engineer at KQED, Inc. in San Francisco, CA and specialize in building full-stack and front-end applications with thoughtful design and intuitive user-experience. I love web development because it enables me to express my creativity while solving technically challenging problems. I am experienced in frameworks and technologies including React/Redux, Angular, Node, Express/Koa, MongoDB, SQL, Elasticsearch, AWS, and HTML/CSS/jQuery.
In my spare-time, I enjoy running, practicing yoga, reading social psychology books, listening to jazz, and traveling. I am passionate about supporting women in STEM and tech, promoting good mental health, and reforming higher education.
Projects
2016 KQED Election Guide
Web and mobile dashboard app that provided voters with election coverage and results for 2016 Bay Area races.
This mobile-optimized web application provided users with a California State Propositions voter guide, Bay Area county voting information, KQED and NPR election coverage articles, and real-time results for over 800 races and measures for nine Bay Area counties.
Built using React/Redux, Node/Koa, Redis, MySQL, and Elasticsearch
How Hipster Is This Coffee Shop?
Satirical web app that determines the hipster-ness of top coffee shops in San Francisco.
This product determines the "hipster-ness" of the top coffee shops in San Francisco by calculating the frequency of certain hipster-related words in Yelp reviews. Users can search for any coffee shop and receive the percentage of reviews that contain words, such as "wood", "natural lighting", and "macbook".
Built using AngularJS, Node/Express, and MongoDB
moodlet
Interactive web journal that enables users to document and visualize their thoughts and feelings.
Users are prompted to reflect on how they are feeling every time they log in. Users can record and track their emotions and thoughts over time as well as view them in a journal or on a graph.
Built using AngularJS, Node/Express, and PostgreSQL
BeautyStash
Social web application that leverages big data to allow users to catalog and share cosmetic products, recommendations, and media.
With this application, users can track specific beauty products by searching for and adding them to different lists (currently own, finished, and wishlist). The app also makes recommendations to users and allows them to visualize their own beauty products. Furthermore, users can follow other users and recommend them products as well as search for and add their favorite beauty articles and blogs.