Flagship projects
Flagship projects in sustainable development
A collection of interdisciplinary AI and data science projects in sustainable development
Combining rapid evidence synthesis and expertise for threatened ecosystem recovery
This project is developing a novel approach to supporting evidence-based decision-making in conservation management. Drawing on tools for rapid evidence synthesis and expert consultation in the health sciences, researchers are creating a standardised approach that can efficiently identify effective management actions to address important conservation problems. Initial case studies are focused on threatened woodlands and peatlands in Australia.
Project team
- Dr Jessica Walsh, Faculty of Science
- A/Prof Peter Bragge, Monash Sustainable Development Institute
- Dr Joslin Moore, Faculty of Science
- Dr Carly Cook, Faculty of Science
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AI and Machine Learning for predicting species responses to global change
This project brings together advances in biological modelling, Machine Learning, and Artificial Intelligence to determine whether alternative low-cost data sources combined with new multi-paradigm modelling techniques can transform our capacity to predict and manage biological responses to global change.
Project team
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Sustainable mix design of concrete using Artificial Intelligence
Concrete is one of the most widely used man-made materials, with a broad range of applications in the construction of buildings, dams, bridges, and pavements. A typical concrete mixture uses energy and natural resources, and importantly, the production of every tonne of cement releases about a tonne of CO2 into the air. To produce sustainable concretes and reduce the pressure on natural resources, waste and by-product materials have been widely used in the production of different types of concrete. Compressive strength (CS) is one of the most important factors in the mix design of concretes, however laboratory-based methods for determining CS are time-, resource-, and labour-consuming.
Alternatively, mathematical equations and empirical expressions can be used for determining the CS of concrete. For this purpose, we are applying statistical methods and artificial intelligence (AI) techniques to develop predictive models for the estimation of CS.
Project team
- Associate Professor Mehrdad Arashpour, Faculty of Engineering
- Professor Tim Dwyer, Faculty of Information Technology
- Dr Emadaldin Mohammadi Golafshani, Faculty of Engineering
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AI for estimating global bushfire smoke and its health burden
Our planet is facing more frequent, longer and unprecedented bushfires under climate change. Severe bushfire seasons have occurred recently in Australia, Canada, and the United States, and there are ongoing fires in the Amazon rainforest attributable to a combination of climate change and deforestation practices. Bushfires are responsible for substantial economic and environmental damage as well as human health risks, as smoke engulfs not only urban areas but also regional areas that have less infrastructure to detect harmful smoke levels. Our aim is to apply AI for estimating the concentrations of bushfire smoke across the world, and its global health burden, which is a vital prerequisite for guiding policy and the public health response.
Project team
- Professor Yuming Guo, Faculty of Medicine, Nursing and Health Sciences
- Associate Professor Zongyuan Ge, Faculty of Engineering and Monash eResearch Centre
- Associate Professor Shandy Li, Faculty of Medicine, Nursing and Health Sciences
- Associate Professor Jiangning Song, Faculty of Medicine, Nursing, Health Sciences
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Advanced monitoring of the SDGs using AI and data technologies
This transdisciplinary project helps public decision-makers tackle complex public problems by using AI in new and innovative ways. We are undertaking social and policy research to understand the needs and concerns of decision-makers to ensure the AI solutions we develop address these, while at the same time building AI tools that analyse data and generate actionable insights in ways that empower decision-makers to make evidence-informed decisions and support the achievement of sustainable development.
Project team
- Prof Rob Raven, Monash Sustainable Development Institute
- Prof Geoffrey Webb, Faculty of IT
- Prof Michael Mintrom, Faculty of Arts
- Prof Rob Skinner, Monash Sustainable Development Institute
- Prof Ann Nicholson, Faculty of IT
- Ms Julie Boulton, Monash Sustainable Development Institute
- Ms Lynn Miller, Faculty of IT
- Dr Paul Satur, Monash Sustainable Development Institute
- Mr Ross Pearson, Faculty of IT
- Dr Steven Mascaro, Faculty of IT
- Dr Mitzi Bolton, Monash Sustainable Development Institute
Predicting flood risk: The case of the Citarum River, Indonesia
Flooding has devastating effects, bringing loss of life, homes, property, mobility and livelihoods and in developing cities brings disease, pests, food and clean water shortages. Flooding is an escalating challenge due to urbanisation and climate change. Traditional approaches for flood prediction use high quality flood data as inputs to complex hydrodynamic models. Developing countries without quality data need new tools to support disaster planning and responses. Our project is exploring the technical feasibility of using satellite data and machine learning to predict flooding of the Citarum River in West Java, Indonesia, one of the planet's most heavily populated and polluted rivers.
Project team
- Dr Klaus Ackermann, Faculty of Business and Economics
- Dr Jane Holden, Monash Sustainable Development Institute and Faculty of Art, Design and Architecture (MADA)
- Dr Christian Urich, Faculty of Engineering
- Dr Dwinanti Marthanty, Civil Engineering, Universitas Indonesia
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Net zero precincts: Citizen data commons and technological sovereignty
Local sustainability initiatives often lack meaningful community engagement in data governance. This project developed a novel participatory approach to enable multiple stakeholders to co-design and co-appraise data governance prototypes in the context of the Monash Net Zero Precinct. Results reveal the importance of harnessing community engagement to reflect the contexts, values and interests of diverse stakeholders and empower multilevel participation in data governance.
Project team
- Dr Sarah Goodwin, Faculty of IT
- Dr Darren Sharp, Monash Sustainable Development Institute
- Prof Rob Raven, Monash Sustainable Development Institute
- A/Prof Liton Kamruzzaman, Faculty of Art, Design and Architecture (MADA)
- Dr Misita Anwar, Faculty of IT
- Prof Lyn Bartram, School of Interactive Arts + Technology, Simon Fraser University
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Flagship projects in health sciences
Monash has a long history of excellence in the health sciences. Using AI & data science to inform our research, we are changing millions of lives for the better.
Flagship projects in better governance and policy
By working across humanities, social sciences, and the STEM sector, we are pioneering discussions for ensuring AI has a positive influence on governance and policy.
Engage with us
We are actively seeking to engage with government, industry and international partners to roll out ground-breaking research solutions in AI and data science.