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2026 ARDC Annual Survey is now open!

The Australian Research Data Commons (ARDC) invites you to participate in a short survey about your interaction with the ARDC and use of our national research infrastructure and services. The survey will take approximately 5 minutes and is anonymous. It’s open to anyone who uses our digital research infrastructure services including Reasearch Link Australia.

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Field of Research : Artificial intelligence
Scheme : Discovery Early Career Researcher Award
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  • Active Funded Activity

    Discovery Early Career Researcher Award - Grant ID: DE240100149

    Funder
    Australian Research Council
    Funding Amount
    $462,044.00
    Summary
    Adaptive and Efficient Robot Positioning Through Model and Task Fusion. This project aims to create fit-for-purpose positioning systems that continuously adapt to diverse and changing environments. The project expects to contribute to the knowledge across robotics, computer vision, and neuromorphic computing. Expected outcomes of this project include ground-breaking place recognition techniques that address two fundamental limitations in the state-of-the-art: continuous adaptation, critically im .... Adaptive and Efficient Robot Positioning Through Model and Task Fusion. This project aims to create fit-for-purpose positioning systems that continuously adapt to diverse and changing environments. The project expects to contribute to the knowledge across robotics, computer vision, and neuromorphic computing. Expected outcomes of this project include ground-breaking place recognition techniques that address two fundamental limitations in the state-of-the-art: continuous adaptation, critically important in safety-critical systems, and energy efficiency, critically important in resource-constrained systems. This should provide significant benefits, such as accelerated deployment of mobile robots, drones and augmented reality solutions in manufacturing, defence, healthcare, household, and space.
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    Active Funded Activity

    Discovery Early Career Researcher Award - Grant ID: DE230101281

    Funder
    Australian Research Council
    Funding Amount
    $329,278.00
    Summary
    An Efficient Computational Solver for Complex Engineering Problems. This project aims to address significant gaps in the existing knowledge about solving complex engineering problems that involve conflicting objectives and unquantifiable features. In these problems, the decision-maker is interested in knowing high-quality and dissimilar solutions that determine the trade-off between the problem objectives. The intended outcomes of this project include a novel robust computational solver that can .... An Efficient Computational Solver for Complex Engineering Problems. This project aims to address significant gaps in the existing knowledge about solving complex engineering problems that involve conflicting objectives and unquantifiable features. In these problems, the decision-maker is interested in knowing high-quality and dissimilar solutions that determine the trade-off between the problem objectives. The intended outcomes of this project include a novel robust computational solver that can automatically find such solutions. The decision-makers can then choose the final solution based on their expertise and preferences. This expects to offer significant benefits to diverse engineering disciplines by finding superior and more practical solutions to their complex multidisciplinary problems.
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    Active Funded Activity

    Discovery Early Career Researcher Award - Grant ID: DE230100761

    Funder
    Australian Research Council
    Funding Amount
    $430,504.00
    Summary
    Identifying biases in news using models of narrative framing. This project aims to develop tools to detect biased narratives and one-sided framing in news stories using novel natural language processing methods to understand the text more deeply. Unlike existing methods, which overly rely on surface word co-occurrences patterns, the novel methods will be able to capture narratives in a more holistic and intuitive manner. Expected outcomes include new modeling techniques grounded in theory and a .... Identifying biases in news using models of narrative framing. This project aims to develop tools to detect biased narratives and one-sided framing in news stories using novel natural language processing methods to understand the text more deeply. Unlike existing methods, which overly rely on surface word co-occurrences patterns, the novel methods will be able to capture narratives in a more holistic and intuitive manner. Expected outcomes include new modeling techniques grounded in theory and a tool to highlight biases with recommendations for diverse sets of news articles. By raising awareness to biased news reporting, the project will benefit Australians through more balanced public discourse on global challenges, such as climate change and health pandemics.
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    Active Funded Activity

    Discovery Early Career Researcher Award - Grant ID: DE240101049

    Funder
    Australian Research Council
    Funding Amount
    $432,485.00
    Summary
    Modeling the Diffusion of Evolving Rumours in Social Networks. This project aims to model the complex evolution and diffusion process of evolving rumours in social media. This project expects to develop new theories and associated techniques from operational research (adaptive genetic algorithms), mathematics (network theory), and machine learning (generative adversarial networks) to tackle the challenges in this project. This project aims to develop (1) novel models for the evolution of a rumou .... Modeling the Diffusion of Evolving Rumours in Social Networks. This project aims to model the complex evolution and diffusion process of evolving rumours in social media. This project expects to develop new theories and associated techniques from operational research (adaptive genetic algorithms), mathematics (network theory), and machine learning (generative adversarial networks) to tackle the challenges in this project. This project aims to develop (1) novel models for the evolution of a rumour, (2) novel models for the diffusion of an evolving rumour, and (3) techniques for detecting the diffusion sources of the original rumour and its mutations. This not only will constitute a major advancement in the theory and application of rumour study but also lead the decision-makers in debunking rumours.
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    Active Funded Activity

    Discovery Early Career Researcher Award - Grant ID: DE240101245

    Funder
    Australian Research Council
    Funding Amount
    $445,047.00
    Summary
    Automated Modelling Assistance for the Creation of Complex Planning Models. Artificial Intelligence (AI) planning technology is used to control systems like automated factories, robots, or to solve complex optimisation problems. Creating these models is however rather complex and error-prone and requires experts to create them in the first place. This project aims at developing techniques and tools for automated modelling support. They will make the modelling process easier and guarantee desired .... Automated Modelling Assistance for the Creation of Complex Planning Models. Artificial Intelligence (AI) planning technology is used to control systems like automated factories, robots, or to solve complex optimisation problems. Creating these models is however rather complex and error-prone and requires experts to create them in the first place. This project aims at developing techniques and tools for automated modelling support. They will make the modelling process easier and guarantee desired model properties such as the desired system behaviour. The tools will thus contribute towards making the technology more easily accessible to companies that might want to deploy them, while reducing costs for doing so and increasing the quality of these models.
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