Aditya Arora

I am a 2nd year Computer Engineering Student at the University of Waterloo, graduating in May 2022.

I have previously worked as a Data Engineer at DraperAI and as an Undergraduate Research Assistant under Prof. Karray to build a intelligent bot to make it easier for customers at Canada's most popular grocery chain to find what they need.

I am an avid follower of all things Artificial Intelligence, be it the advantages of AI in the medical industry to the misuse of it to generate fake photos of celebrities.

Data is my best friend and I like to gather insights from datasets that I can find online!
[You can see a sample of my work here or ask some of my friends at DraperAI]

In the past I've been a core member of the computer vision subteam at WATonomous, the University's autonomous driving student design team as well as the Web Lead at Waterloop, the university's hyperloop team

Some of my previous experience

Data Engineering, DraperAI
Waterloo, ON.
Jan 2019 - April 2019


- Reduced customer conversion time by 15% by building a tool to entice new customers
- Improved bid accuracy by 30% by analysing suggesting changes to core bidding algorithm
- Found 3 high priority production issues affecting 10% of our marquee customers
- Built an internal tool to detect and alert system downtime using SQL and Metabase

Chief Technology Officer, Sage Co
Waterloo, ON.
May 2018 - Present


- We're a digital agency run by active University of Waterloo students from across the globe. We aim on creating excellent digital solutions for clients on a professional scale.
- Responsible for guiding the technological direction of the company, to ensure that we have 100% uptime!

Undergraduate Research Assistant, University of Waterloo
Waterloo, ON.
September 2018 - December 2018


- Built a NLP chatbot in Python and Dialogflow for grocery chain Loblaws under Prof Fakhri Karray to allow customers to ask contextual questions while in store
- Ported over existing from slower excel sheet frameworks to PostGresQL to improve net performance by 30%
- Developed a low latency API endpoint in Python from scratch to serve Loblaws customers

Data Scientist + Full Stack Developer, LCBO|next
Kitchener, ON.
May 2018 - September 2018


- Wrote complete CRUD web apps and REST APIs from scratch with less than 0.1% downtime to serve data to multiple internal applications to serve LCBOs customers
- Managed and maintained the sole Kubernetes cluster running an Elasticsearch instance
- Implemented an 85% accurate sales forecasting model from scratch to anticipate uptick in sales of products after incorporating the weather forecast
- Visualised and analysed sales trends at top retail locations to classify products into priority based classes to support LCBO’s retail and supply chain divisions

Core Perception Member, WATonomous
Waterloo, ON.
January, 2018 - May, 2018


- Core Member of the perception team as part of GM’s AutoDrive Challenge
- Implemented a 5% more effcient model to identify lane markings in OpenCV
- Improved existing traffic sign detection computer vision models in Tensorflow by 15% using hyperparameter tuning and regularisation

Web Co-Lead, Waterloop
Waterloo, ON.
September, 2017 - March, 2018


- Redesigned the entire new website as part of revamped branding in Fall 2017 with the help of Embedded JS templating on a Node.js server
- Minimized code duplication on the new website using a template engine that allowed for 30% page load boost while making it easier to maintain
- Improved page load time by 20% by creating responsive vector images in D3.js instead of using heavier and less efficient frameworks
- Implemented an efficient static string method to improve memory management as part of the embedded systems team

Software Engineering Intern, FINO Bank
Mumbai, India.
Summer, 2017.


- Improved efficiency of backend script by 300 times by using hash tables and used this to implement an interactive dashboard to visualise revenue of top merchants and their sales breakdown
- Conceptualised, designed and implemented a dashboard to track the performance of new merchants month on month to predict merchants who had a better chance to increase the revenue
- Used d3js for the visualisation and Python for the back end.

Side Projects

Kaggle logo

Kaggle
Data science stuff, rudimentary machine learning plus data analysis on various datasets

leetcode

LeetCode
Although not a project per se but it does the job of making me a better programmer

Slackr

slackr
Command line slack clone made by programming sockets in Python

WaterlooWorks v2.0 logo

WaterlooWorks v2.0
It adds better searching, filtering of jobs and modernizes the UI of the current platform to scale to both and tablets

Blogs