Space and Information Technology
Data Intensive Astronomy

The Data Intensive Astronomy (DIA) research group at the UWA Node of the International Centre for Radio Astronomy Research, led by Professor Andreas Wicenec, brings a unique mixture of internationally recognised expertise in space-relevant computer science topics, including:

• Machine learning and deep learning on general image and video object recognition, detection and classification, also applied to more general problems like time series analysis and general optimisation problems.
• Development and operation of very large scale, globally distributed data management systems, including remote areas and space.
• Exa-scale distributed processing software systems: These systems have been deployed and processed data on the largest super-computers in the world and very diverse platforms, including small and large scale cloud systems.
• Development and optimisation of algorithms and generic solvers.
• Development of large scientific software applications using modern professional software development practices and following strict delivery schedules. We have a pool of people practicing and certified in the Scaled Agile Framework (SAFe) for very large distributed agile development projects.

Their space-relevant projects include:

• Various radio astronomy projects, including the Square Kilometre Array, Murchison Widefield Array, Australian SKA Pathfinder as well as data reduction and support projects for the wider community.
• Projects in computer vision, object detection and classification.
• Ocean swell prediction improvement.
• Gravitational wave detection.
• Previous involvement in various satellite projects including HIPPARCOS, DIVA and GAIA.