An accessibility app that plans a UofT student's day around light sensitivity, deadline pileups, tight budgets, or burnout, and won 1st place in the advanced track at UofTHacks' Hack or Treat. Its “Zombie mode” low-energy planner extracts a student's ACORN timetable from a PDF or screenshot with in-browser OCR, then minimizes walking using indoor connections, transit, and precomputed distances. Deterministic TypeScript planning logic is kept separate from the React UI, with routing data precomputed offline so plans generate instantly with no API calls.
TypeScriptReactNode.jsVitestOCR
A real-time multiplayer fantasy soccer platform where friends snake-draft players from a live fixture and score points from that match. Built with React, Fastify, and Socket.IO, with PostgreSQL for persistent game and draft data and Redis to keep draft rooms synced live and handle reconnects. Supports live scoring for drafts, trades, and power-ups on one standard point system, tested with simulated match data. Prototyped in Figma, with the server as the source of truth so every player stays in sync.
ReactFastifySocket.IOPostgreSQLRedis
A full-stack running route generator that creates loop routes from any starting point and target distance, pulling in OSRM routing, Photon geocoding, Open-Meteo elevation, and Overpass traffic-signal data. An iterative route-fitting algorithm places waypoints on a circle and nudges each one inward or outward to land routes within 8% of the target distance, while several layouts are generated in parallel with asyncio and the best is picked by a weighted score (distance accuracy, U-turns, doubling back). Prototyped in Figma, then built as a responsive map-first app with autocomplete search and an elevation chart.
PythonFastAPIasyncioJavaScriptLeaflet.js
Pearson Airport Taxi Optimization
A machine learning project that optimizes aircraft taxiing at Pearson Airport. A CNN-based model is trained on real flight data to predict runway congestion before aircraft land, and those predictions are used to dynamically reroute gate taxi paths away from high-traffic areas, reducing overall ground-movement delays. Built for the Industry 4.0 Case Competition, which it went on to win.
PythonMachine LearningNumPyGeoPandas