Kieran Ricardo
Research Software Engineer - Atmospheric Modelling at ACCESS-NRI
Canberra, Australia
Summary
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Rockstar🎓
Top SchoolKieran Ricardo is a Research Software Engineer in atmospheric modelling based in Canberra with eight years' experience at the intersection of geoscience, data science and machine learning. He has built production and research software across government and research organisations including ACCESS‑NRI, Geoscience Australia and CSIRO Data61, and contributed core graph neural network components (APPNP/PPNP) and examples to the well-known StellarGraph library. With dual degrees in Mechatronics (First Class Honours) and Mathematical Modelling from ANU, he blends strong mathematical foundations with practical engineering to tackle node‑level ML problems and environmental hazards such as wind risk. Colleagues rely on him for turning research algorithms into robust, reusable code—often revealing value in how model propagation and graph representations improve domain forecasts.
8 years of coding experience
5 years of employment as a software developer
Australian National University
Github Skills (5)
keras10
machine-learning10
tensorflow10
graph-convolutional-networks10
python10
Programming languages (7)
Github contributions (5)
stellargraph/stellargraph
Sep 2019 - Jun 2020
StellarGraph - Machine Learning on Graphs
Role in this project:
ML Engineer
ML EngineerContributions:1 release, 178 commits, 121 PRs in 8 months
Contributions summary:Kieran contributed to the implementation of the APPNP and PPNP layers and models, adding functionality to propagate any keras model with APPNP. The contributions are focused on node classification tasks using graph convolutional networks. Furthermore, they improved the Deep Graph Infomax example.
pythonheterogeneous-networkssaliency-mapfraud-preventiongraph-machine-learning
ACCESS-NRI/CMEPS
Jun 2023 - Mar 2025
NUOPC Community Mediator for Earth Prediction Systems
Contributions:3 reviews, 5 PRs, 18 pushes in 1 year 8 months
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