R

Robert Amour

Full Stack Developer

Hi! I'm Robert (or Bobby).

I like playing piano, cooking, baking, and making awesome software.

I spent a few years pursuing a degree in music before deciding my interest in computer science and programming was more than just a hobby. A few toy projects and one Barnes-Hut N-body simulator later, I decided to pursue programming with a renewed vigor.

I love simple, functional design with great UX — and I believe everything needs a dark theme.

Projects:

eFerret (React Native version)

December 2022 - Present

Get it on Google Play

eFerret is a cross-platform React Native app and modern web app (eFerret.io) for finding great deals and rare items on eBay. Utilizing live data from the eBay API, it notifies users of interesting items within seconds after they are posted.

I created eFerret in 2017 to assist with my (at the time) vintage fountain pen restoration hobby. Now, hundreds of people around the world use it to find the best deals on eBay and locate hard-to-find inventory for their businesses.

  • Top 30 highest-grossing Shopping apps of 2024
  • 5000+ installs on Google Play
  • ~ 200 daily active users, 300 monthly
  • Drives over $1.6 million in sales to eBay each year
  • Processes ~1 million eBay API requests per day
Technologies used:
React Native
Python / Django + Postgres

dChan - Q Origins Project archives

June 2021 - present

On behalf of the Q Origins Project, I created the largest archive of QAnon content that exists today. With over 19,000,000 posts from the Q boards on 4chan, 8chan, and 8kun, as well as 1.3 million posts from Reddit's QAnon communities before they were banned site-wide in 2018, this archive provides much-needed data to extremism experts, researchers, and scholars of this underrepresented field.

Utilizing specialized Scrapy spiders, the project automatically scrapes relevant content from 8kun in realtime, providing vital insights on online extremism. Posts are saved in a Postgres database and processed into an Elasticsearch index for rapid search and time series analysis.

Technologies used:
Python / Django
Postgres + Elasticsearch
Scrapy
Pandas
React + d3

“Where in the World is Q? Clues from Image Metadata”

By Abigail W. Xavier, Robert Amour and the Q Origins Project (@QOrigins)

January 2021 - May 2021

As part of the Q Origins Project, I helped discover the first forensic evidence of the whereabouts, and thus identity, of “Q”, the anonymous online persona behind the QAnon conspiracy theory.

Along with a professional data scientist and a QAnon subject matter expert, I participated in a detailed investigation of metadata on images posted by the anonymous imageboard user “Q” who had been gaining an increasingly alarming grip on U.S. politics since emerging in late 2017.

Our investigation successfully located Q's activity to several known time zones including Pacific and UTC+8 (Asia), greatly narrowing down the pool of potential suspects. Our investigation was published in Bellingcat after a lengthy and thorough review and fact checking process.

  • Worked as part of a three-person team who made this discovery and wrote up our findings
  • Created data visualizations telling the story of our data
Technologies used:
Python
Pandas
React + d3 (for the interactive dataviz, visible here; source here)

Quærendo

May 2020 - September 2020

On May 4, 2020, as hospitals worldwide were being hit with the first wave of COVID-19 in a pandemic that would kill more than one million Americans, a video called "Plandemic" was released online. Full of false claims and disinformation, it created a wave of panic and skepticism against already flimsy trust in public health authority in the United States.

Within days, the video went viral and attracted millions of views, as medical experts and the fact checking community lagged behind. Some people resorted to sharing informal fact-checks from experts on social media platforms such as Reddit and Twitter. This made clear the need for faster, democratized fact checking. A few days later, the Quærendo project was born.

Quærendo was my naive attempt at kicking off a new, democratized form of social media fact checking. I abandoned this project when Twitter rolled out Community Notes (née Birdwatch), as I thought it was a (similar, but!) superior solution.

Frontend:
React
Backend:
Django + Postgres

Typometry

October 2018 - June 2020

Typometry is a web app for improving typing speed at all levels by assessing typing characteristics and seamlessly delivering personalized exercises.

Typometry is my attempt at hacking touch typing. As the backend receives granular typing data, simple, corrective exercises are generated in realtime to fix the "weakest link" in the user's typing technique. This way, a typist with a non-traditional typing style does not have to start from scratch learning which fingers go where.

Frontend:
React
Backend:
Django + Postgres

eFerret (Original Android version)

December 2017 - December 2022

Get it on Google Play

The original version of my now cross-platform app. Many users suffered humored my whimsical UI and graphic design and made this a surprisingly popular app despite my best efforts.

  • 5000+ installs on Google Play
Technologies used:
Java (native Android)
MySQL (eventually replaced with Postgres)
Flask / Python (eventually replaced with Django)

Heatwave (Freelance)

April 2018 - June 2021

"Project Heatwave" - A data-driven analysis of global warming using atmospheric radiation emission data from NASA's AIRS program. This project gathers and analyzes a large dataset from the NASA AIRS satellite using Pandas and Numpy. Heatwave is a fully open-source project by Chris Rentsch.

  • Implemented major feature additions and bug fixes over the course of several years/
  • Resulted in several rehires by the client for additional features, fixes, and consultation.
Technologies used:
Python
Pandas
Numpy

This website was built from scratch using React and Material-UI and is itself open source!