I'm pursuing a Bachelor of Computing in Computer Science at the University of Guelph, specializing in Artificial Intelligence with a Business minor. My background combines software engineering, data analytics, and AI, with a focus on building full-stack applications with robust architecture, scalable backends, and intuitive frontends. The intersection of AI and business is also a key interest of mine, especially using data, automation, and intelligent systems to improve decision-making, create better products, and turn technical ideas into practical value.
Incoming Fall 2026.
Analyzed client and transaction data to support AML, fraud, and financial crime investigations through risk-based reviews and case documentation.
Developed a high-performance Python data migration tool and built full-stack Shopify integrations using Remix, deploying scalable solutions to AWS.
Taught snowboarding and skiing to all age groups, focusing on safety, tailored instruction, and clear communication.
Designed and maintained IT systems, managed web assets, supported financial tracking, and handled customer-facing storage operations.
I built Token Atlas to make next-token generation easier to see. It runs a 494M-parameter open-weight model, maps its 151,665-token vocabulary in 3D, and streams each decision into an interface where candidates, probabilities, attention links, and the completed path can be inspected and replayed.
I built GitZero as a Python CLI that scans local folders or public GitHub repositories for signals consistent with AI-generated or AI-assisted code. It combines 25+ git-history and static-code signals, explainable risk scoring, false-positive guards, JSON/CSV exports, and an optional calibrated Random Forest probability.
I built a credit risk scoring project using the UCI Credit Card dataset, which contains 30,000 customer records with demographic, financial, and repayment history data. The goal was to explore real world credit behavior, uncover patterns in default risk, and build a model that can predict which customers are more likely to default on their next payment.
I parsed and explored a large-scale financial transaction dataset using SQL, then modeled account relationships as a transaction network in Python with NetworkX. The project combines graph analytics, risk scoring, and Power BI visualizations to surface suspicious clusters, central accounts, and fund-dispersion patterns commonly associated with AML investigations.
Built at GDSCHacks 2025, TravelPal is a green AI-powered trip planner that generates personalized, eco-conscious itineraries with Gemini. My team built a full-stack app with Next.js, Convex, Clerk, Vapi, and carbon-aware planning features to help users understand the environmental impact of each trip.