News

Our Future World, a once-in-a-decade global megatrends report by CSIRO, identifies seven pathways to the challenges and opportunities that will shape our future in the next twenty years. Amongst the seven megatrends are: Adapting to Climate Change; Leaner, Cleaner and Greener; and Increasingly Auton...

This week saw the release of the long-awaited State of the Environment report authored by Prof Emma Johnson AO, USYD’s new Deputy Vice-Chancellor, Research, Dr Ian Creswell and Dr Terri Janke. The report outlines the significant challenges ahead for managing the pressure of climate change......

We are delighted to welcome our six new Chief Investigators who have recently joined the DARE team. They are experienced researchers with proven track records of multi-disciplinary research and industry collaborations, and sought-after mentors and HDR Supervisors.   Prof John Close, Australian ...

On Thursday 17th February 2022 we presented our 2nd annual DARE Symposium. 7 Investigators from the DARE Training Centre presented to a hybrid audience across Australia. Partner Investigators from McKinsey & Co and WaterNSW joined our researchers in showcasing how Data Science is Solving Domain....

The DARE 2022 Symposim: Data Science Solving Domain Problems is just a week away. The DARE ARC Training Centre is taking on the grand challenges that face Australia’s biodiversity, mineral and water domains by taking a multidisciplary data science approach. Previously an in-person event, the.....

DARE ARC Centre was proud to be a Gold Sponsor of the 24th International Congress on Modelling and Simulation (MODSIM2021) held from December 5-10 at the University of Sydney and International Convention Centre Sydney. The conference was a hybrid event with over 150 in-person attendees......

Congratulations to our team on their latest achievements: Tongliang Liu had the following 4 papers published in NeurIPS Confident-Anchor-Induced Multi-Source-Free Domain Adaptation Instance-Depdendent Label-Noise Learning under Structural Causal Models Probabilistic Margins for Instance Reweighting ...