•, some experiments with storytelling and generative arts.
  • CeleritasML, a collection of machine learning related projects.
  • box2box, a repository of sports analytics experiments.


  • Basketball Analytics and Beyond: Analysis of 188,946 Shots (2021). Portfolio.
  • xG visualization pipeline (2021). Blog. Twitter. GitHub.
  • tarantino (2021). A color palette based on Quentin Tarantino’s movies. Blog. GitHub.
  • @canberramapbot (2020). A Twitter bot posts bird’s-eye views over Canberra periodically. GitHub. Twitter.
  • sentRy (2020). A telegram bot monitoring Django error logs. Blog. GitHub.
  • aussie (2019). Scraped over 76,000 courses offered by some top Australian unis in 2020. GitHub.
  • pokeswapR (2019). Random color swapping between Pokémons. Blog. GitHub.
  • A Theoretical Recap of Big Data (2018). In this project we considered how to test hypotheses about covariance matrices and, since everything “eighties” is trendy again, we looked at some multivariate time series papers from that epoch and make them fresh again. There are interesting connections between these two topics. The aim of the project is to take the modern viewpoint and understand what happens in both situations when the dimensionality p of the observations becomes large. GitHub. Report.
  • Mining and Predictions on Australian Stock Prices (2018). Applied associate mining on Australian stock data within R package rattle to discover frequent patterns. At the same time constructed models using regression, neural network and time series to predict the future stock price change. GitHub. Report.
  • Bayes Premier League Prediction (2018). Our group conducted a presentation based on the paper Bayesian hierarchical model for the prediction of football results by Gianluca Baio & Marta Blangiardo. Bayesian hierachical model for Premier League prediction. We introduced both base model and hierarchical model, compared the results of the two, discussed the limitation and possible improvement of them. Gist. Slide.
  • Westerosi Survival Report (2017). Using Bayesian approach to extract the vital factors that determine a character’s fate based on GRRM’s A Song of Ice and Fire (Vol. I to V). GitHub. Report.
  • Chicago Insurance Redlining (2017). A quite naïve exploratory analysis on Chicago insurance data set. Report.