Hi there 👋, I'm Dillion!
I'm a 5th year CS / BBA student 🎓 studying at the University of Waterloo and Wilfrid Laurier University. I've also interned as a software engineer 👨💻 at Shopify, Nvidia, Splunk, and Lime.
My current interests include distributed systems, concurrent and parallel programming, artificial intelligence and product management.
Please check out my open source projects in my portfolio for some examples of my work.
Reach out to me at 👉 hello@dillionverma.com
# Work Experience
# Education
University of Waterloo
Honours Bachelor of Computer Science (BCS), Co-op
2016 - 2021
Wilfrid Laurier University
Honours Bachelor of Business Administration (BBA)
2016 - 2021
White Oaks Secondary School
International Baccalaureate Diploma
2014 - 2016
# Featured Projects
Facial Sentiment Intensity Analysis (Undergraduate Research Paper)
June 2020 - August 2020Developed and trained a Deep Convolutional Neural Network (DCNN) on the ADFES-BIV facial emotions dataset to predict the intensity of human emotions with an average final prediction accuracy of 86% on unseen data.
Links
Meme Exchange
August 2019 - June 2020Developed an online platform which allows users to buy and sell memes for a profit 💰. This project was completed individually on and off over the span of 10 months and is the cumulative result of all my frontend and backend web development learning until now.
Links
Ricepay
January 2018 - August 2018Co-founded and developed an online platform which allows users to order and pay for meals at restaurants using only their mobile devices.
Links
Sorcery
November 2017 - December 2017Developed Hearthstone (a popular online card game) for the terminal completely from scratch using C++. Implemented many design patterns including Observer pattern (for board and players), Decorator pattern (for enhanced abilities of cards), and MVC pattern (for code structure).
Links
EndlessBlock
June 2017Developed a python library which can be imported into any python game and change the difficulty of the game based on the real-time emotion of the player. Uses OpenCV and webcam for facial recognition, and a custom machine learning model trained on a Kaggle facial emotion dataset using Tensorflow and Keras. This project recieved 1st place prize at the Global AI Hackathon - Toronto and was also invited to demo at NextAI Canada.
Links
PocketDoc
May 2017Developed at University of Waterloo's Equithon, Pocketdoc is an app where you can take a picture of your physical wound, and it returns suggested medicines or cures for the injuries or diseases identified in the wound. This project also placed as a top 10 finalist at Makeschool's Global App Competition 2017.