The UNSW Data Science Hub (uDASH) is a major strategic initiative of UNSW Science. It aims to cultivate and promote foundational and applied research in Data Science with a focus on environmental, physical and health sciences. The Hub provides a world-class environment, with access to state-of-the-art data visualisation and computing facilities. These facilities enable the creation, development and deployment of transformative data-driven decision-making tools that help us to address future societal challenges.
uDASH involves the participation of multiple Schools within UNSW Science and across UNSW, and also collaboration with industry and government. It operates via four pillars:
Building and developing the foundations of Data Science methodology and creating next-generation inferential and analytical techniques.
Solving challenging problems through the analysis and modelling of data. We provide expertise to enable data-informed decisions to benefit industry, government and society.
Education & Outreach
Empowering communities through the use of Data Science methods and training. We enhance skillsets through educational programs and motivate the next generation of Data Scientists.
Enabling and accelerating cutting-edge research in the environmental, physical and health sciences, using novel and bespoke Data Science tools.
Professor Scott Sisson is the Director of the UNSW Data Science Hub. He is internationally-recognised for his work in computational and Bayesian statistics, particularly for developing inferential techniques for computationally intractable models and challenging data.
Scott is also a Deputy Director of the ARC Centre of Excellence for Mathematical and Statistical Frontiers.
He is a recent President of the Statistical Society of Australia. Previously, Scott was awarded the P.A.P. Moran Medal (Australian Academy of Science), the G. N. Alexander Medal (Engineers Australia) and the J. G. Russell Award (Australian Academy of Science) for Outstanding Research.
Interested in becoming an industry partner or collaborating with uDASH?
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