- Posted on 3 Jun 2025
Innovative machine learning tools that predict water quality in advance has taken out an Australian Financial Review Artificial Intelligence Award.
UTS has been recognised with one winner and four finalists at the annual Australian Financial Review AI Awards, which celebrate ground-breaking achievements in AI and the industry leaders and innovators in the field.
The winning tools predict the water quality in the dams, rivers and creeks that feed into drinking water supply supplying four million residents in Sydney and Melbourne. The project won in the Sustainability category.
“As machine learning and AI advance, we recognised their potential to tackle more dynamic variables during extreme weather that demand real-time, adaptive solutions,” says Distinguished Professor Fang Chen, Executive Director of the UTS Data Science Institute and project lead.
Our expertise in asset diagnostics now underpins our work to predict water quality shifts before they compromise safety. We’re thrilled to be recognised by this important national award.
UTS had three other finalists in the Australian Financial Review AI Awards:
Community engagement: Guide Dogs NSW/ACT and UTS Robotics Institute partnership developing robotic mobility aids for vision impaired and blind people.
Ethics and transparency: Invisible Bystanders project from the UTS Human Technology Institute on how workers are becoming invisible in organisation’s transitions to using AI.
Research and education: the UTS Australian Artificial Intelligence Institute and their ground- breaking research and innovation programs.
UTS is a global knowledge leader in AI, being ranked 36th in the world for the field in the 2025 QS subject rankings and home to three major research centres specialising in AI.
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UTS data scientists have built cutting-edge machine learning tools that predict water quality in the dams, rivers and creeks that feed into our drinking water supply.
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UTS data scientists have built cutting-edge machine learning tools that predict water quality in the dams, rivers and creeks that feed into our drinking water supply.
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Researchers have developed a new AI algorithm, called Torque Clustering, that is much closer to natural intelligence than current methods. It significantly improves how AI systems learn and uncover patterns in data without human guidance.
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