PROJECTS
Dev Core Social Networking Service
Built with: MongoDB, Express, React, Node.js, Redux, Material-ui, Mongoose, Axios, Webpack
● Created a social
networking site where junior developers can learn, grow, and
collaborate together.
● Coded the back-end using
various Node.js packages and MongoDB in creating a RESTful api.
○ Utilized Express for efficient, performant routing and act as the
backbone for this RESTful api.
○ Implemented Mongoose to simplify modeling and interaction with MongoDB.
● Constructed the front-end
to be clean, responsive, and deliver the best user experience using React and Material-ui.
○ Managed app level state with Redux to allow users to have seamless interaction
with all components.
○ Bundled using Webpack to better customize polyfill behavior and in general to make a
leaner product.
Pokemon Card Web App
Built with: JavaScript, HTML, CSS
● Produced a responsive and
accessible web app to become a teaching example to help my siblings learn.
● Programmed specifically in vanilla JavaScript
to demonstrate manipulating DOM, calling asynchronously to api, and
caching can all be achieved without frameworks/libraries.
● Painstakingly crafted the stylesheet
in vanilla CSS to reveal the underlying mechanic behind a responsive site
with media queries.
● Proceeded to write the entirety of HTML to
showcase how to manually optimize for SEO and follow WCAG.
Personal Profile Page
Built with: jQuery, Bootstrap, JavaScript
● Launched a web page which has a clean and
responsive UI inorder to showcase a personal profile.
● Leveraged Bootstrap and jQuery to
create a responsive, quick, and efficient static page.
● Lighthouse metrics illuminates that
this site has a 96 performance rating on both desktop and mobile platforms.
Flappy Bird Clone
Built with: HTML5 Canvas, JavaScript
● Assembled a clone of “Flappy Bird” which
uses HTML5 Canvas to render the game.
● Applied knowledge of revealing module pattern
to minimize namespace pollution and being able to make customized
modules to change the behavior of the game (eg. a module was created to lock framerates).
Semi-Supervised Fuzzy K-Means Clustering
Built with: scikit-learn, Python
● Developed with scikit-learn in Python to analyze label frequencies of
'money-fx,' 'interest,' and 'trade' in past Reuters articles.
● Devised semi-supervised fuzzy k-means algorithm strategies with the use of scikit-learn's TfidfVectorizer.
● Discovered that 'money-fx' yielded the most stable results. With a precision of 0.602 and recall of 0.672 seems to suggest
that the strategies devised caught most and accurately the frequency of 'money-fx' when compared to other labels.
TECHNICAL SKILLS
Languages:
JavaScript,
HTML,
CSS,
Java,
Python,
OCaml,
CLISP,
C/C++,
Libraries/Frameworks:
React,
Express,
Axios,
Mongoose,
Redux,
Material-UI,
jQuery,
Bootstrap,
scikit-learn
Other:
Node.js,
npm,
MongoDB,
MySQL,
Webpack,
git,
Arch Linux
EDUCATION
University of California, Los Angeles
December 2017
Bachelor of Science in Computer Science
EXPERIENCE
JL Design and Build
October 2019
● Employed at a construction
firm which specializes in tenant improvement of small restaurants.
● Usual tasks include overseeing
night crew and ensuring inspections to run smoothly.
● Current holder of CSLB B
license for general building contractor (#1026504).