App Link: chasethechicken.pages.dev

About the Project: What It Is & How It Works
Chase the Chicken is a real-world urban hide-and-seek web application that fuses high-stakes tag mechanics with battle-royale shrinking zones and nightlife precinct discovery. Players gather in an urban precinct, scan a room QR code to enter a synchronized multiplayer lobby, and divide into competing squads: the elusive Chickens and the pursuing Hunters.

Once the match begins, Chickens must stay within dynamically shrinking precinct boundaries, navigate between local venues, and complete stealth photo check-ins to stay ahead of the hunters. Hunters track them across an interactive map using periodic location intel, zone shrink timers, and pub radar. The match concludes when hunters physically verify a chicken tag or the chickens survive the final zone collapse, with all players receiving full match recaps and photo vaults.

Technology Stack & Architecture
Built as a progressive web application with React 18 and Vite, the interface utilizes custom Vanilla CSS design tokens for ultra-responsive styling, fluid micro-animations, and full light/dark mode support. Interactive geospatial mapping is powered by Leaflet and OpenStreetMap (Nominatim), featuring custom non-concentric boundary slicing algorithms for dynamic zone shrinkage.

Real-time device synchronization is driven by Supabase Realtime broadcast channels and PostgreSQL with hardened Row-Level Security (RLS) policies. Deployed on Cloudflare Pages with automated CI/CD and strict Content Security Policies, the architecture adheres to a privacy-by-design framework: player locations exist purely in-transit without persistent tracking breadcrumbs, uploaded check-in proofs auto-purge after 24 hours, and venue foot-traffic analytics remain strictly anonymized.

Live Website: fozprints.com.au

The Background
I started Foz Prints to solve a problem I had with my own Subaru Forester SG. The factory interior plastics become brittle over time. Original replacements are either discontinued or ridiculously expensive, and most aftermarket options look terrible. I decided to design, model, and manufacture my own 3d printed replacement parts in Sydney, printing them in heat resistant ASA plastic so they can actually survive an Australian summer.

The Tech Stack
I wanted full control over the design and speed of the website, so I built a headless setup instead of using a standard template.

• Frontend: A custom Next.js site hosted on Netlify.
• Backend: Shopify to handle the secure checkout, inventory management, and payments.
• DNS: Cloudflare to route traffic safely between the two systems.

The Build Process and Challenges
Handling both the physical product engineering and the web development at the same time threw up some interesting roadblocks.

• The Prototype Graveyard: Getting a 3D printed part to perfectly match a twenty year old dashboard is incredibly difficult. It took dozens of CAD iterations to get the curves, snap fits, and surface textures exactly right before the parts looked like they actually belonged in the car.
• Headless Routing: Connecting a Next.js frontend to a Shopify checkout was a difficult task. I had to correctly map the root domain to Netlify while isolating the secure checkout on a Shopify subdomain without taking the whole site offline.
• Working Around Locked Code: To keep running costs low, I used the basic Shopify Starter plan. This meant the backend code was completely locked down. When the headless setup caused the checkout logo to trap users on a dead end page, I could not use custom JavaScript or third party apps to fix it. I had to build native navigation workarounds to get customers back to the main site.
• Australia Post API Limits: Getting live shipping rates to work at checkout was another massive headache. The Australia Post API is incredibly strict. If a single product weight, box dimension, or suburb spelling was slightly off, the whole checkout would crash. Figuring out exactly how to format the data to keep the API happy took a lot of trial and error.
• Leveraging AI as a Technical Partner: Building a custom web platform alone is tough, so I heavily utilised AI tools throughout the project. I used AI to help write custom code, debug Next.js routing bugs, and translate confusing Shopify documentation. Having an AI to bounce ideas off drastically sped up the troubleshooting process, especially when fixing weird DNS and API connection issues.

Infrastructure & Host Overview
Built on an HP EliteDesk 800 G5 featuring an Intel i7 processor, this self hosted server operates as a centralised, high availability compute and storage hub for custom web applications, automation pipelines, and containerised services. The system is managed via CasaOS and Docker Compose, providing a resilient, isolated environment for hosting internal services without cloud lock in or recurring SaaS subscriptions.

Centralised PostgreSQL Database Layer (tracker_db)
At the core of the server's data architecture is a containerised PostgreSQL instance serving as the central relational backbone across multiple custom microservices. Rather than scattering data across disparate SQLite files or third party cloud SaaS platforms, the system enforces structured schema isolation within a unified database:

• tax schema: Backs the custom Tax Dashboard, storing categorised deduction records, multi year asset depreciation schedules, vehicle trip logs, and income statements.
• lifestats schema: Ingests high frequency lifestyle telemetry, GPS coordinates, event timestamps, and photo metadata with multi user isolation.
• finance schema: Maintains transaction ledgers, portfolio snapshots, asset balances, and historical pricing feeds.
• Reliability & Backups: Implements automated database dumps and snapshot routines, ensuring high throughput, ACID compliance, and full data sovereignty under local control.

Australian Tax & Deduction Automation Dashboard (FastAPI & PostgreSQL)
A full stack compliance and analytics platform tailored to Australian Taxation Office (ATO) regulations for both PAYG employment and sole trader activities:

• Custom Tax Engine: Automatically calculates deductions, marginal tax bracket liabilities, and Medicare levy thresholds across financial years.
• Asset Depreciation Calculator: Computes multi year asset write offs using both Prime Cost (straight line) and Diminishing Value methods with customisable effective life spans and claimable percentages.
• Vehicle & Travel Logbook: Tracks business kilometres and travel deductions compliant with ATO logbook methods.
• Excel & Receipt Pipeline: Ingests historical deduction spreadsheets (Tax Deduction.xlsx) via an automated import pipeline and supports receipt file attachments stored in containerised volumes.

Life Stats Tracker & Telemetry (PWA & Analytics Viewer)
A real time personal telemetry logging system designed for fast, seamless habit and lifestyle tracking on the go:

• Offline First Mobile PWA: Built with responsive HTML5, modern CSS, and a Service Worker (sw.js) allowing instantaneous single tap logging from mobile devices even without active internet connectivity.
• GPS Geolocation & Media Logging: Records precise geolocation coordinates for activity heatmaps and supports photo uploads (such as culinary steak logs, daily routines, and entertainment tracking).
• Resilient Backend Server: Powered by a lightweight Python server (stats_server.py) with dynamic database driver management (supporting both psycopg2 and pg8000) and automated local CSV fallback.
• Interactive Visualisation Engine: Features a dedicated analytics dashboard (stats_viewer.html) displaying geographic heatmap distributions, chronological activity timelines, category breakdowns, and streak statistics.

Investment & Finance Analytics Dashboard (Flask & Background Workers)
A custom web application built with Python Flask and containerised in Docker on port 8095 for end to end investment monitoring:

• Multi Asset Portfolio Tracking: Aggregates equities, ETFs, crypto holdings, and cash reserves into unified net worth calculations and allocation breakdowns.
• Asynchronous Market Data Pipeline: Uses threaded background workers (background_worker.py) and an intelligent caching layer (cache_storage.py) to pull live market valuations and currency conversions without degrading UI responsiveness.
• Historical Analytics: Generates interactive profit/loss reports, yield projections, and performance charts against market benchmarks.

Zero Trust Secure Remote Access (Tailscale)
All self hosted dashboards and services are securely accessible anywhere in the world via a Tailscale Zero Trust VPN mesh. By utilising WireGuard-based point to point encryption, all server ports remain completely closed to the public internet, eliminating attack vectors while providing low latency remote connectivity across mobile phones, laptops, and workstations.

Smart Home Orchestration, Document Authoring & Media Ecosystem
Beyond custom telemetry and financial tools, the server hosts:

• Smart Home Hub: Home Assistant and a dedicated Matter Server coordinating IoT devices locally with zero cloud reliance.
• Overleaf / ShareLaTeX: A private, containerised collaborative LaTeX editor for authoring academic and technical engineering documentation locally.
• Media Suite: Jellyfin and Jellyseerr for private high definition streaming, hardware transcoding, and automated metadata curation.

This professional ePortfolio website represents a modern approach to web development, combining traditional programming skills with cutting edge AI collaboration tools. The project showcases my ability to effectively leverage Large Language Models (LLMs) and AI assisted development workflows to create a polished, responsive web presence.

Throughout the development process, I utilised multiple AI platforms including ChatGPT, Google Gemini, and Claude to explore different design approaches, troubleshoot issues, and refine the user experience. Each LLM brought unique strengths to the project. From generating initial HTML/CSS structures to optimising responsive layouts and suggesting best practices for web accessibility.

A key aspect of this project was my experience with GitHub Copilot's agent based workflow. Rather than simply accepting code suggestions, I approached the development process as a project manager, assigning specific tasks and roles to AI agents, reviewing their proposed changes, and iteratively refining the output. This workflow involved:

• Task Delegation: Breaking down complex features into specific, well defined tasks for AI agents
• Code Review: Critically evaluating AI generated code for quality, maintainability, and alignment with project goals
• Iterative Refinement: Providing feedback and requesting modifications to achieve the desired outcome
• Version Control: Managing changes through Git to maintain a clear development history

The project also enhanced my skills in web technologies (HTML5, CSS3, JavaScript), responsive design principles, UI/UX considerations, and Git version control. By treating AI as a collaborative tool rather than a replacement for critical thinking, I developed a workflow that maximises productivity while maintaining high code quality and design standards.

This experience has prepared me for the evolving landscape of software development, where the ability to effectively collaborate with AI tools is becoming as important as traditional programming skills. It demonstrates my adaptability, project management capabilities, and understanding of how to leverage emerging technologies to deliver professional results.

I place strong emphasis on attention to detail throughout design and implementation. The site follows a mobile first approach and has been tested across major mobile browsers (Chrome, Safari, Firefox, Edge) to ensure responsive layouts, readable typography, accessible navigation (ARIA attributes and keyboard support), and correct image handling on small screens.

For users who prefer a paper copy, the site's Print controls (the Print link in the top navigation and the print friendly banner) automatically expand all project tiles and ensure photos are included when printing. This provides an easy way to produce a complete, print optimised version of the portfolio that preserves expanded content and images for offline review.

Live Site: korpie15.github.io
GitHub: View Repository

The Turtlebot warehousing robot automates item picking and delivery in warehouses using a scalable system of robots. Initially, a single robot maps the warehouse, creating a static map while avoiding dynamic obstacles like people or forklifts. The system assigns tasks to robots based on proximity and payload capacity, coordinating item retrieval and delivery to a drop off zone. Using lidar, the robots dynamically avoid obstacles, including each other, to maintain efficiency.

My focus was on the payload delivery system, a 3D printed mechanism with a servo driven trap door. Mounted on the top of the robot, it securely carries and dispenses items from the pick up to the drop off zone. Controlled by an Arduino Nano that listens for a signal from the Raspberry Pi the turtle bot is running on. By being mounted above the Lidar the system minimises interference with the lidar for smooth operation.

GitHub: View Repository

This project involved simulating a robotic system with two robots, one of which required designing both its physical and kinematic models. The system was tasked with performing a pick, place, and sorting operation to organise blocks by colour. This included a GUI, obstacle detection, and a physical emergency stop button that worked in both simulation and on real hardware. A RealSense camera was used for vision, providing both colour and depth data.

Through this project, I gained a deeper understanding of robotics mathematics, including kinematics and singularity errors. This insight connected theory to my practical experience as a control systems engineer, where I had recently encountered similar challenges with Fanuc robots. Learning the theory behind why robot joints cannot align straight, to avoid singularity errors, was particularly valuable as it directly addressed a real world problem I had faced.

In AI in Robotics, my group project was to program an AI model that could play Tetris. We successfully achieved this goal.

The Tetris AI project uses Deep Q Networks (DQN) and reinforcement learning to optimise gameplay. The AI evaluates the best moves based on board metadata, enabling it to plan for combos like "Tetris clears" while minimising gaps and towers. It generalises well across board sizes, such as a 30x20 grid, despite training exclusively on a standard 10x20 grid. By analysing final states instead of individual moves, the model achieves efficient, adaptable, and high-performing gameplay.

Live Demo: Play Tetris AI
GitHub: View Repository

This group project involved leveraging the Boston Dynamics SPOT robot for search and rescue operations in challenging and potentially hazardous environments. We developed a ROS1 package to facilitate autonomous exploration and human detection, making the system accessible for anyone to install and use. The onboard video feed from SPOT was integrated with YOLOv3 for human identification, achieving a confidence threshold of 80%. Since the pre trained human detection model met our needs, no additional model training was required. When a human was detected, a marker was placed on a global map, allowing rescuers to pinpoint their exact locations.

Exploration of the environment utilised a greedy frontier based algorithm, ensuring complete area coverage. Once SPOT finished exploring, the total number of markers on the map provided the rescue team with a clear overview of all detected individuals and their locations.

This project was also a significant learning experience for me. It marked my first exposure to ROS, Linux, and Git repositories, helping me build confidence in installing and integrating different packages into robotic projects. These new skills have expanded my technical capabilities and prepared me for future projects.

Open source humanoid robot build project for UTSMechSoc to engage members and showcase at open days.

The THOR robot project was undertaken as a society initiative to provide hands on learning opportunities for members while creating an impressive display piece for university events. This open source build allowed students to gain practical experience in mechanical assembly, electrical systems, and robotics integration.