Rob Hyndman
Professor at Monash University
Melbourne, Victoria, Australia
Summary
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RockstarRob Hyndman is a professor and seasoned statistical software developer based in Melbourne with 17 years of experience building robust forecasting tools and open-source methods. He develops new time series methodology and implements it in widely used R packages—most notably contributing core ETS and Box-Cox functionality to the influential forecast package. Equally at home in teaching and engineering, he creates course materials and polished LaTeX/R Markdown outputs, including custom CV templates and forecasting slides that bridge pedagogy and reproducible code. His work emphasizes stability, modular design, and practical accuracy improvements, reflecting a strong focus on reliable production-ready analytics. Beyond papers and packages, he contributes thoughtful usability enhancements (contact/skills sections, formatting) that show attention to end-user experience often overlooked by academics.
17 years of coding experience
Stackoverflow
30,975reputation
4.4mreached
485answers
9questions
layout
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image
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dataframe
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Github Skills (31)
layout10
beamer10
image10
r10
time-series10
cvs10
vector10
forecasting10
latex10
resume10
rmarkdown10
forecast10
bookdown10
data-analysis10
aggregate9
Programming languages (12)
Github contributions (5)
robjhyndman/forecast
Apr 2012 - Jan 2023
Forecasting Functions for Time Series and Linear Models
Role in this project:
Back-end Developer
Back-end DeveloperContributions:29 releases, 1 review, 1429 commits in 10 years 10 months
Contributions summary:Rob made multiple contributions to the core forecasting functions within the package, specifically focusing on the implementation and enhancement of various ETS models, including support for Box-Cox transformations. The user also contributed to the stability and robustness of existing functions, as well as refactoring code for a more modular and extensible design of the forecasting functions. The contributions included fixes for potential errors that could occur during simulations and model fitting as well as improving accuracy calculations.
forecastingr-packagetidymodelscranrstats
robjhyndman/ETC3550Slides
Mar 2018 - Jan 2023
Slides for a forecasting course based on "Forecasting: Principles and Practice"
Role in this project:Full-stack Developer
Full-stack DeveloperContributions:1 release, 337 commits, 7 PRs in 4 years 11 months
Contributions summary:Rob contributed to the development of slides for a forecasting course. Their work involved creating custom LaTeX style files and modifying existing ones, indicating a focus on presentation design and customization. The user added R code for chapters 2 and 3, as well as toolbox examples, further showing a hands-on approach to the course material. This suggests the user was involved in both the design and implementation of the course slides and code examples.
forecastingmeteorologypythonprinciplesgarden
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