Partner with us
Australia has an impressive and expanding footprint in data science research and training. However, this footprint is spread over a large continent; the field of data science is very fast-moving; demand for data science capability and capacity is still exploding; and there is increasing interest not only in individual groups but also in collective and national profiles.
To provide a more comprehensive and inclusive solution, we have established the Australian Data Science Network (ADSN). The ambition is clearly and deliberately to enhance and expand opportunities and outcomes for all members of the Network.
The Australian Research Council (ARC) Centre of Excellence for Mathematical and Statistical Frontiers (ACEMS) engages in research programs that combine innovative methods for the analysis of data with theoretical, methodological and computational foundations, provided by advanced mathematical and statistical modelling.
The Australian Institute for Machine Learning (AIML) is Australia’s first institute dedicated to research in machine learning. AIML's world-class research strengths lie in machine learning and the methods that support this; artificial intelligence, computer vision and deep learning.
The Australian Mathematical Sciences Institute (AMSI) is the collaborative enterprise of Australia’s mathematical sciences. It exists to give independence to the enterprise's disciplines and provide infrastructure so that members can take initiatives on the national and international stage. AMSI's aim is to improve the levels of mathematical capacity and facility in the Australian community.
The Data Science Research Unit (DSRU) at Charles Sturt University focuses on machine learning, machine vision, cybersecurity, simulation and modelling, computational intelligence and robotics, data mining, astronomical and space sciences as well as the application of these fields to real-world problems
The Centre for Data Analytics and Cognition at La Trobe University focuses on the theoretical advancement of artificial intelligence (AI) as well its practical contributions to organisations, the economy and society. We specialise in research and development of cutting-edge AI algorithms and Data Analytics platforms.
Monash Data Futures Institute is your access point to the breadth of Monash University's expertise in Artificial Intelligence and Data Science for social good. Our interdisciplinary research focuses on AI and data science across three themes: health sciences, better governance and policy, and sustainable development.
Monash University's Department of Econometrics and Business Statistics is connecting research and education for a deeper understanding of econometrics and business statistics. They are ranked among the best business schools for econometrics and business statistics, including their world-leading Forecasting Unit.
Queensland University of Technology (QUT)'s Centre for Data Science draws together capability in data science from across Australia to deliver world-class research, unique training opportunities and active external engagement. QUT is the lead node for the Australian Data Science Network.
RMIT's Centre for Information Discovery and Data Analytics (CIDDA) specialises in developing new approaches to find relevant information in massive data collections. CIDDA establishes a capability for processing the enormous volume of data produced by new technologies.
The Statistical Society of Australia aims to further the study, application and good practice of statistical theory and methods in all branches of learning and enterprise. The national Society represents Australian and overseas statisticians providing the focus and organisation of local activities.
Swinburne's Data Science Research Institute leads the data-to-discovery pathway for data-intensive research in biology, physics, astronomy, economics and social sciences. We address the grand challenges of industry with expertise in big data, data analytics, machine learning and artificial intelligence (AI).
The Melbourne Centre for Data Science is built out of a joint collaboration between Statistics and Computer Science at the University of Melbourne. The Centre's goal is to promote and engage in fundamental and interdisciplinary research, teaching and leadership in Data Science by forging a vibrant, research rich and engaging interdisciplinary environment to lead advances in data science.
The UNSW Data Science Hub 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.
The University of South Australia's Data Analytics Group (DAG) primary focus is on extracting actionable information from complicated data to help decision making and automation. Their research topics include data mining, predictive modelling, data management, and multimedia information systems.
The Centre for Translational Data Science is unleashing data’s transformational potential at the University of Sydney and beyond. The Centre is leading new advances in the physical, life and social sciences through research and the application of data and machine learning technologies, operating as a partnership between data scientists and researchers.
The UTS Statistics and Data Science group has interests that range from the development of fundamental statistical methods to the application of statistics in such areas as population health, forensics, and law. A major part of our work involves the development of new methodology to investigate complex problems in the age of Big Data.
The University of Wollongong's National Institute for Applied Statistics Research Australia (NIASRA) is committed to developing and applying innovative statistical methods to important problems. It undertakes a range of fundamental and contract research, major consulting projects, and professional education in statistical methodology.
Yoni Nazarathy is senior lecturer at the School of Mathematics and Physics (SMP) at the University of Queensland (UQ). His academic research lies in the field of operations research, applied probability, stochastic models, queueing systems, parameter estimation, scheduling and control.