Hey there! I'm Edward, a software engineer in the payments space. I'm passionate about building high-impact software.
Recently, I've been avidly following F1 and the incredible technology behind the sport. I've also been playing some chess.
Feel free to reach me at edwhuang (at) umich (dot) edu or at the form below!
October 2019 - April 2020
• Developed website served on Amazon Web Services displaying electrocardiograms (ECG) to improve accessibility for Michigan Medicine doctors to thousands of patient ECG records
May 2019 - July 2019
• Implemented website registration functionality for proposed construction projects and review system for approval of projects serving
millions of users
• Identified, documented, and fixed bugs through testing of website and created mockups for new features
July 2018 - September 2018
• Achieved MVP peer-to-peer food delivery iOS application in 12 weeks
• Designed and implemented Uber/Lyft-style map UI using Google Maps API, online shopping flow, and facilitated implementation of secure transactions using the Stripe API
An iOS app created for Concordia International School Shanghai's annual Model United Nations conference with over 1000+ attendess to guide participants around campus, push out schedule updates, and provide intros to invited speakers, among other purposes.
Swift, Xcode
Google Chrome extension that allows you to easily manage your tabs bar by grouping tabs together and storing them in a pocket to free up computer memory
HTML/CSS, JavaScript, Bootstrap
A game where you are assigned some target in a lobby of players, and you are aiming to take a picture of your target. If you successfully take a picture of your target, you assassinate the target. The goal is to be the last one standing.
Swift
Python program that takes in a username from Twitter (account must not be locked and have at least one tweet, not including retweets) and downloads up to 3240 of the user's most recent tweets, trains the n-gram language model using the data, and displays a generated tweet
Features include being able to generate tweets using a combination of all downloaded data, and displaying a graph for the most frequently used words
Website for teachers to view feedback and trends regarding their performance over time by automating feedback collection.
Django, Python, HTML/CSS, JavaScript, Bootstrap, ChartJS, Heroku
Website that analyzes the sentiment (positive or negative) of text and images that appear on the news. Text predictions are based on a Scikit-learn support vector machine model trained on 1.6 million tweets, while image predictions are based on a Tensorflow sequential model trained on images from the news scraped off the Web.
Python, Scikit-learn, Tensorflow, Flask, Heroku
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Branding, Illustration
