Hello! I'm Patrick, a computer science graduate from the University of Toronto - Scarborough Campus. I've worked primarily in automation-related roles at Manulife Financial, Seequent, and Inpixon. Now I work as a Senior Cloud Engineer @ Kinaxis!
I enjoy taking on new challenges and transforming ideas into solutions towards problems that come my way. Through my school projects and work experience, I've acquired the skills and knowledge necessary for the industry today - agile methodologies (scrum), testing, object oriented programming, continuous integration, etc. The list doesn't end there since I'm always looking to learn more and add more tools to my [developer] belt!
Apart from my academics, I enjoy lifting weights, playing a bit of guitar on the side, and also drawing!
Ask Finleigh is a chatbot capable of answering questions and queries related to the fintech - financial technology - industry. Individuals have the option between querying through two different ways - through a search engine or through IBM Watson. The front-end was made with React.js using the Material UI library to give it a minimalistic look, Firebase for user authentication/management, and Apex Charts for providing simple visualizations of user querying statistics. The back-end was written in Java using Javalin for managing our webserver/handling events, H2/Requery for database related operations, Apache Lucene for being the indexer component of our search engine, and the IBM Watson Discovery/Assistant APIs. This project received an overall grade of 90%.
Click here for a quick video demo of the projectMyBnB is a small-scale replica of AirBnB's database systems. It supports basic operations of allowing users to rent and host housing listings with specific amenities/details. It also allows for individuals to query for available listings given a select amount of user defined filters. This project was made with Java and MySQL as a console-based application. It received an overall grade of 105%.
Food for Thought is a web application that parses images of food (generally raw/basic ingredients) provided by the user and returns a list of recipes that they can make based on that input. Its back-end was written in Python and Flask (for server hosting). For recognizing the images of food and querying recipes, we used the Google Cloud Vision API and Recipe Puppy respectively.