Math, Stats & CS Student
Building (Data-Driven) Systems & ML Applications
01 / BACKGROUND
Third-year Mathematics, Statistics & Computer Science student at the University of Toronto.
I develop practical solutions at the intersection of mathematics, statistics, and code from implementing machine learning algorithms to building robust backend systems and creating data visualization tools. This portfolio showcases projects spanning ML, quantitative finance, and full-stack development. I am currently developing a sports betting arbitrage system that identifies and executes risk-free betting opportunities across multiple sportsbooks using real-time odds analysis and automated trade execution.
02 / PORTFOLIO
ML-powered cross-exchange funding rate arbitrage system with delta-neutral portfolios
Program that creates short-form content from long-form videos using machine learning
A Python tool used to find real-time arbitrage opportunities between different sports books
A tool that visualizes UofT course prerequisites as an interactive dependency graph
Habit tracking app with streak tracking, calendar visualization, and routine management
Tool for analyzing RBC credit card statements and visualize them in an informative way
Real-time TTC bus tracking and transit news
Dashboard for view of market
Streamlined trade execution CLI for efficient market operations