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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 Nvidia, Splunk, and Lime.


My current interests include distributed systems, concurrent and parallel programming, artificial intelligence and product management.

Through previous internships, startup work, and personal projects, I've accumulated extensive technical experience in:

  • Web Development (React/Redux + Typescript, Vue.js, Node.js, Python, Rails)
  • Mobile Application Development (Android, iOS, React Native)
  • Cloud Infrastructure Providers (AWS, GCP, Digital Ocean, Firebase)
  • Container Orchestration (Docker, Kubernetes)
  • Machine Learning (Artificial Neural Networks, Convolutional Neural Networks, Decision Trees, and Bayesian Classifiers using Python, Tensorflow, and Keras)

Please check out my open source projects in my portfolio for some examples of my work.


I am looking for internships for winter (Jan 2021 - Apr 2021) or summer (May 2021 - Aug 2021).

Check out my resume here 👉   resume(opens new window)

Reach out to me at 👉   hire@dillionverma.com

Schedule a call with me 👉   here(opens new window)


# Work Experience

  • Nvidia

    Software Engineer

    Jan 2020 - Apr 2020 • 4 months
    Santa Clara, California
  • Splunk

    Software Engineer

    Jan 2019 - Apr 2019 • 4 months
    San Jose, California
  • Lime

    Software Engineer

    Jan 2018 - Apr 2018 • 4 months
    San Francisco, California
  • Mitre Media

    Fullstack Web Developer

    May 2017 - Aug 2017 • 4 months
    Toronto, Canada

# Education


Facial Sentiment Intensity Analysis (Undergraduate Research Paper)

June 2020 - August 2020

Developed 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.

Python
Jupyter Notebook
Tensorflow
Keras

Links

Meme Exchange

August 2019 - June 2020

Developed 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.

Vue.js
Ruby on Rails
PostgreSQL
Redis
Firebase
AWS
Docker
Kubernetes

Links

Ricepay

January 2018 - August 2018

Co-founded and developed an online platform which allows users to order and pay for meals at restaurants using only their mobile devices.

React
React Native
Ruby on Rails
PostgreSQL
Redis
Firebase
AWS

Links

Sorcery

November 2017 - December 2017

Developed 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).

C++

Links

EndlessBlock

June 2017

Developed 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.

Python
PyGame
Keras
Tensorflow
OpenCV

Links

PocketDoc

May 2017

Developed 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.

React Native

Links


# Hackathons

  • Major League Hacking 2020 Hackathon Season

    HackDavis

    January 20th - 21st, 2018
    Davis, California

    Developed a mobile application which allocates a daily carbon emission allowance to users to move towards a more sustainable environment.

    Best Data Hack

    Links

  • Global AI Hackathon - Toronto

    June 23rd - 25th, 2017
    Toronto, Ontario

    Developed 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 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.

    1st Place Winner

    Links

  • Open Source Circular Economy Days Hackathon

    June 10th, 2017
    Toronto, Ontario

    Developed a custom admin interface for the food waste startup Genecis to manage their data and provide analytics.

    1st Place Winner

    Links

  • Make School's Student App Competition 2017

    May 19th - 21st, 2017
    International

    Submitted PocketDoc to an online app competition and placed top 10 in the world.

    Top 10 Finalist | Honourable Mention

    Links

  • Major League Hacking 2020 Hackathon Season

    StartHacks I

    March 4th - 5th, 2017
    Waterloo, Ontario

    Developed at StartHacks 2017, Recipic is a mobile app which allows the user to take pictures of ingredients around their house, classify those ingredients using the ClarifAI image recognition API, and return suggested recipes to make using the provided ingredients. Recipic recieved 1st place at the hackathon for best pitch and hack.

    1st Place Winner

    Links


# Some cool facts