The Analytics and Decision Sciences (A&DS) program brings together the core research capabilities needed to make rational inferences and predictions from models and/or observations about the world, and it develops methods to use these to make efficient, risk-based decisions. Its core skills are in the statistics, machine learning, computational modelling, optimisation, economics and financial mathematics, computational linguistics, and software engineering disciplines.
One of A&DS’ interests in supporting the transition of the Australian economy through the fourth industrial revolution, is in helping manufacturing and other production systems to develop real-time situational awareness, integrating the diverse data streams in their organisation, to deliver actionable information.
RiskLab Real Options – dynamic decision making under uncertainty
Mining projects are frequently impacted by uncertain financial and geological variables. Dynamic decision making utilising current financial and geological data supports informed operational decision strategies.
A vital component of any optimisation application is its interface. The end-user needs to be able to understand the answer and have confidence that the system is correct. In many applications they also need to be able to guide and tailor the solution to take account of changed circumstances or criteria that are difficult to formalise a priori.
As automation becomes increasingly ubiquitous in everyday life, we investigate the design of systems where the humans and computer-based systems (or machines in the broader sense), co-operate in a functional and safe way. In this sense, we strive to design systems that can account for the human element, and in which the human can leverage his/her natural ability via the appropriate use automation.
Having access to real-time data is of enormous benefit to mental health researchers.
This new information from We Feel will be compared to existing literature to see how social media can be used to contribute to the real-time tracking of mental health in Australia.
This project has provided a prototype tool to support Black Dog Institute researchers to gather evidence on the role of social media in the development of more effective public health campaigns as well as the evaluation of existing campaigns.
We’ve developed a tool called ‘We Feel’ to see if social media can accurately map our emotions and help us better understand mental health.
Emergency Situation Awareness (ESA)
The Emergency Situation Awareness (ESA) system analyses Twitter messages posted during disasters and crises providing time-critical information that allows emergency services to respond rapidly and appropriately.
A powerful, cross-platform scientific workflow framework that enables collaboration and software reuse.
A national fire behaviour knowledge base
We've developed a new computer application that enables the easy calculation of expected fire danger and fire behaviour via a simple easy‑to-use interface.
Water pipe failure prediction
We’re using data-driven techniques to improve prediction of pipe failures for water utilities, saving the industry millions of dollars in maintenance costs.
Monitoring the health of structures
Using sensing, continuous monitoring and advanced data analysis techniques we support civil and industrial asset managers to make more informed maintenance decisions.