Stellargraph: visualising machine learning on graphs

Dr Xavier Ho1

1CSIRO’s Data61, Docklands, Australia

Abstract:

Stellargraph (https://www.stellargraph.io/) aims to solve the world’s data connectivity problems. CSIRO’s Data61 is developing and open-sourced a state-of-the-art graph machine learning library that is being used by other tech giants and companies in their workflow. Stellargraph also has 2 components under private beta: Stellargraph Platform, for scalable machine learning on big data, and Stellargraph Visualisation, for rapid insights discovery, analytics, and reporting.

This talk will focus on the research our Stellargraph team has done in the last 2 years and present selected findings relevant to the scientific data community. We are also interested in collaborating with other institutions who are using graphs or looking to use graphs with machine learning, and will present a few pathways for collaboration.

Stellargraph is part of CSIRO’s Data61 Tech Program, Investigative Analytics.


Biography:

Xavier contributes at the CSIRO’s Data61 in Australia as a software crafter, focusing on real-time data visualisation, creative coding, and interaction design. His work spans across multiple scientific research areas, including Smoke and Fire, Transport Logistics (TraNSIT), and StellarGraph. In November 2019, he obtained his PhD at The University of Sydney in games studies and data visualisation, with a living project Roguelike Universe that seeks to connect the dots.

His interest in the demoscene is new school, influenced by new technology like projectors, audio synthesis, and computer graphics on the web. He collaborated on game jam projects like Golden Fleece, and worked with an audio-visual production installation at Vivid Sydney. He is currently hitting up books and resources around physically-based rendering to go deeper into the graphics rabbit hole.

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