VCFA Summer 7s Fixturing
2024

• Created bespoke fixtures for seven divisions for the summer women’s league. Each division had unique constraints and a timetabling engine was created to optimize fixtures for each of these divisions.
• Key Skills: Python, Optimization, Timetabling & Fixturing.

Academic Timetabling – International House @ The University of Melbourne

2017 — 2022

• Created timetabling algorithms to create the academic timetable for International House.
  • This was a complex problem with over 400 students, 50 subjects, and 20 teachers.
• Solution reduced two weeks of manual work to a few seconds.
• Used for at least five years after creation.
• Key Skills: Python, Optimization, Flask, JavaScript.
• https://github.com/jdgsmallwood/school_timetabling

Primary School Sports League Fixturing
2023

• Created fixtures for a local primary school requiring a fixture for teams of students to play each other in a multi-sport league.
• Each team needed to play each other team in each sport, while providing variety each week in terms of teams played and sports played.
• Key Skills: Python, Optimization, Timetabling & Fixturing.

Fantasy Premier League – Team of the Season Calculation
2023 — 2024

• Calculated the perfect team of the season for local competition, satisfying league constraints.
• Key Skills: Python, Optimization.

UV Warnings Melbourne – Telegram Bot
2024

• Created a Telegram bot which provides warnings when UV goes above 3, reminding you to be sunsmart!
• Key Skills: AWS Lambda, Web Scraping, Python.
• https://github.com/jdgsmallwood/uv-warning-telegram-bot-lambda

Brownlow Medal Prediction
2014 — Current

• Predicts the winner from each team in the Brownlow Medal count from game-by-game statistical data.
• Key Skills: Python, Machine Learning, Web Scraping, Optimization, Postgres, Docker.

Flute Scale Dashboard
2021-2022

• Tracks the tempo of scales practiced, and suggests scales that you have not practiced recently.
• Created a Shiny dashboard with a Google Sheets backend to plot changes over time.
• Key Skills: R, Shiny, Dashboarding.
• https://github.com/jdgsmallwood/music-scales-dashboard

The Statistics of Monopoly
2014

• Constructed a statistical model of the expected return from each property in Monopoly using Markov Chains and R.
• Published an article “Roll the Dice!” based on this work in the University of Melbourne Farrago.
• Done in conjunction with Dhanuka Nanayakkara.
• Key Skills: Statistical Modelling, R.

Limit Order Book Modelling
2015 — 2017

• Completed as the research component of the Master of Science (Mathematics & Statistics) with Professor Konstantin Borovkov receiving a high distinction.
• Analyzed tick-level data from the Australian Stock Exchange to construct an algorithm to reconstruct the limit order book at any point in time.
• Modeled the evolution of the limit order book and proved that order arrival rates could not be Markovian.
• Key Skills: Python, R, Statistical Modelling.

Drift Estimation on a Spatial Lattice
2013 — 2014

• Completed as a summer research project with the Australian Mathematical Science Institute, supervised by Dr. Owen Jones.
• Created methods to estimate the drift of observed stochastic processes using the crossing tree method.
• Key Skills: R, Statistical Modelling.

Lux AI
2021

• Created an agent to compete in the LuxAI Kaggle competition.
• Utilized a rules-based approach to attempt to optimally extract resources & expand cities.
• Implemented A* path-finding for agent movement.
• Key Skills: Python, Algorithms.
• https://github.com/jdgsmallwood/lux_ai