The Great Sushi Race

Tech stack: Nextjs, MongoDB, Zustand, Pixi.js

The weekly meetings at one of my previous companies relied on traditional charts and spreadsheets to communicate quarterly revenue performance across sectors, making it difficult for teams to quickly grasp their progress relative to goals.
I designed an interactive dashboard that visualized sector performance as a race between Australian animals, where each animal's position represented how close that sector was to hitting quarterly targets. This transformed dry financial reporting into an engaging visual that made performance gaps immediately apparent to leadership and motivated teams through friendly competition.

Technical highlights: Large-scale React architecture, real-time data visualization with Pixi.js, optimized state management for smooth animations.

Statistical Pairwise Comparison Ranker

Tech stack: Built using: Vue, Nuxt, PostgresSQL, Vercel,

Most ranking systems break down when comparing fundamentally different categories—how do you fairly rank Batman against a Toyota Corolla? I built an application that uses ELO rating algorithms to handle these "apples to oranges" comparisons, revealing unexpected patterns in human preference hierarchies.
The system generates a dynamic network graph showing relationship clusters between unlikely items (Nicolas Cage cardboard cutouts vs. wet socks vs. the Ghostbusters film), creating a visual map of how people actually make irrational comparison decisions. This exploration into comparative psychology demonstrates how statistical models can extract meaningful insights from seemingly nonsensical data.

Technical highlights: ELO rating implementation, dynamic graph visualization, statistical analysis of irrational decision patterns.