Towards a cognitive process model of how attention and choice interact. Before making any decision, we must gather information on what options are available. This process may influence the choices we make: if we do not notice an option, we will not choose it even if it would have been valuable. This project aims to examine how prior experience can produce attentional biases that influence decisions, and will develop a new computational model of this interaction of attention and choice as an outc ....Towards a cognitive process model of how attention and choice interact. Before making any decision, we must gather information on what options are available. This process may influence the choices we make: if we do not notice an option, we will not choose it even if it would have been valuable. This project aims to examine how prior experience can produce attentional biases that influence decisions, and will develop a new computational model of this interaction of attention and choice as an outcome. This new knowledge will enhance the world-class status of Australian cognitive psychology. Moreover, it should provide significant benefits through improving our ability to predict and shape behaviour, and shedding light on the role of biases in healthy cognition and in the context of compulsive behaviours.Read moreRead less
Tracking towards a complete model of skilled reading comprehension. This project aims to promote the development of the first complete computational model of reading comprehension. Many computational models of sub-components of reading have been developed, but none fully explain the complex co-ordination of perceptual, attentional and cognitive processes required for successful comprehension. The project intends to use eye tracking studies to test and refine Über-Reader, a new computational mode ....Tracking towards a complete model of skilled reading comprehension. This project aims to promote the development of the first complete computational model of reading comprehension. Many computational models of sub-components of reading have been developed, but none fully explain the complex co-ordination of perceptual, attentional and cognitive processes required for successful comprehension. The project intends to use eye tracking studies to test and refine Über-Reader, a new computational model that aims to provide a complete account of the memory systems and cognitive processes involved in reading comprehension and how they differ with reading skill. The outcomes will advance understanding of the causes of success and failure in reading and contribute to diagnosing and remediating reading difficulties.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE210100115
Funder
Australian Research Council
Funding Amount
$328,092.00
Summary
Living to tell, telling to live: Experience, narrative, and the self. A robust sense of self is crucial for our mental wellbeing. This sense of self, philosophical research shows, is constituted by our experiences and the socio-culturally shaped stories we tell about us. However, the fundamental role of these self-narratives remains poorly understood: are they merely retrospective accounts of our experiences, or can they influence them? By analysing the biological underpinnings of the human mind ....Living to tell, telling to live: Experience, narrative, and the self. A robust sense of self is crucial for our mental wellbeing. This sense of self, philosophical research shows, is constituted by our experiences and the socio-culturally shaped stories we tell about us. However, the fundamental role of these self-narratives remains poorly understood: are they merely retrospective accounts of our experiences, or can they influence them? By analysing the biological underpinnings of the human mind and defining the core features of self-narratives, this project will lead to a novel theory about the sense of self. This theory will enhance our understanding of the power of self-narratives and has the potential to provide theoretical foundations for future applied research on the self and its disturbances.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE230100206
Funder
Australian Research Council
Funding Amount
$423,154.00
Summary
Pain: Open to interpretation? This project aims to determine how pain interpretation drives pain experience, using rigorous state-of-the-art lab research. This project expects to generate new knowledge about the psychological mechanisms maintaining pain experience and avoidance behaviour, using novel techniques to measure interpretation of pain sensations. Expected outcomes include the development of an evidence-based psychological model of pain interpretation, enhanced capacity to build interna ....Pain: Open to interpretation? This project aims to determine how pain interpretation drives pain experience, using rigorous state-of-the-art lab research. This project expects to generate new knowledge about the psychological mechanisms maintaining pain experience and avoidance behaviour, using novel techniques to measure interpretation of pain sensations. Expected outcomes include the development of an evidence-based psychological model of pain interpretation, enhanced capacity to build international collaborations, and ecologically valid methods for measuring pain interpretation. This research forms a solid platform for further translational research, to build novel, scalable interventions to improve outcomes for the one in five Australians living with chronic pain.Read moreRead less
Australian Laureate Fellowships - Grant ID: FL220100061
Funder
Australian Research Council
Funding Amount
$3,147,256.00
Summary
Literacy in adolescence: The next major challenge in the science of reading. This project aims to address the pressing problem of why Australian secondary school children have been declining in literacy. To do so is crucial, since adolescence is a period when strong literacy is critical for knowledge acquisition and preparation for adult life. The project will use a range of theoretically-informed methods to scrutinise cognitive processes in adolescent reading, as well as identify interactions b ....Literacy in adolescence: The next major challenge in the science of reading. This project aims to address the pressing problem of why Australian secondary school children have been declining in literacy. To do so is crucial, since adolescence is a period when strong literacy is critical for knowledge acquisition and preparation for adult life. The project will use a range of theoretically-informed methods to scrutinise cognitive processes in adolescent reading, as well as identify interactions between reading progress and socio-emotional functioning and motivation. Expected outcomes will be the first comprehensive account of secondary school reading acquisition and new insights into how to optimise progress. These will inform research, policy, and reading instruction practice, to the benefit of Australia's children.Read moreRead less
Modelling Adversarial Noise for Trustworthy Data Analytics. Adversarial robustness is a core property of trustworthy machine learning. This project aims to equip machines with the ability to model adversarial noise for defending adversarial attacks. The project expects to produce the next great step for artificial intelligence – the potential to robustly explore and exploit deceptive data. Expected outcomes of this project include theoretical foundations for modelling adversarial noise and the n ....Modelling Adversarial Noise for Trustworthy Data Analytics. Adversarial robustness is a core property of trustworthy machine learning. This project aims to equip machines with the ability to model adversarial noise for defending adversarial attacks. The project expects to produce the next great step for artificial intelligence – the potential to robustly explore and exploit deceptive data. Expected outcomes of this project include theoretical foundations for modelling adversarial noise and the next generation of intelligent systems to accommodate data in a noisy and hostile environment. This should benefit science, society, and the economy nationally and internationally through the applications to trustworthily analyse their corresponding complex data. Read moreRead less
Excellent researchers: Using learner profiles to enhance research learning. Recent evidence concerning metacognitive learning and affect reveals that research degree candidates are a diverse group of learners, and little is known about explaining wasteful attrition, stress and delays in progress. Such a study is essential, especially given the growth in research degrees, new transitional pathways, diversity in candidate backgrounds and chronic high attrition. This longitudinal study applies new ....Excellent researchers: Using learner profiles to enhance research learning. Recent evidence concerning metacognitive learning and affect reveals that research degree candidates are a diverse group of learners, and little is known about explaining wasteful attrition, stress and delays in progress. Such a study is essential, especially given the growth in research degrees, new transitional pathways, diversity in candidate backgrounds and chronic high attrition. This longitudinal study applies new findings about doctoral learning profiles in a direct intervention (DOCLearnPro) that targets individual differences across students in doctoral and master’s degrees to improve learning outcomes significantly and contribute theoretically, methodologically and substantively in order to advance understanding of researcher development.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE230100495
Funder
Australian Research Council
Funding Amount
$422,154.00
Summary
Structured Federated Learning for Personalised Intelligence on Devices. The project aims to develop a new structured federated machine-learning framework to enhance the customisation of artificial intelligence across mobile and smart devices. It seeks to enable users to receive customised services on their devices without sending their sensitive personal data to a cloud service provider. Anticipated benefits include greater privacy, data security and device performance, as well as better end-use ....Structured Federated Learning for Personalised Intelligence on Devices. The project aims to develop a new structured federated machine-learning framework to enhance the customisation of artificial intelligence across mobile and smart devices. It seeks to enable users to receive customised services on their devices without sending their sensitive personal data to a cloud service provider. Anticipated benefits include greater privacy, data security and device performance, as well as better end-user experience. Expected outcomes of this research include new knowledge, toolkits and algorithms for use in developing machine-learning based secure, efficient and fault-tolerant technologies for software applications, mobile services, cloud computing, autonomous vehicles and advanced manufacturing processes.Read moreRead less
Toward Human-guided Safe Reinforcement Learning in the Real World. This project aims to investigate human-guided safe reinforcement learning (RL). Safe RL is an important topic that could enable real applications of RL systems by addressing safety constraints. Existing safe RL assumes the availability of specified safety constraints in mathematical or logical forms. This project proposes to study learning safety objectives from information provided directly by humans or indirectly via language m ....Toward Human-guided Safe Reinforcement Learning in the Real World. This project aims to investigate human-guided safe reinforcement learning (RL). Safe RL is an important topic that could enable real applications of RL systems by addressing safety constraints. Existing safe RL assumes the availability of specified safety constraints in mathematical or logical forms. This project proposes to study learning safety objectives from information provided directly by humans or indirectly via language models, and human-guided continuous correction for safety improvements. The established theories and developed algorithms will advance frontier technologies in AI and contribute to a wide range of real applications of safe RL, such as robotics and autonomous driving, bringing enormous social and economic benefits. Read moreRead less
Self-supervised feature learning for rapid processing of marine imagery. Fast and reliable quantitative estimates of marine environmental health are needed for scientific studies, design and management of protected areas, and regulatory compliance of industrial activity in the ocean. Australia is collecting seafloor images at increasing rates but expert annotations are not keeping up, meaning that typical machine learning approaches struggle. This project will develop self-supervised techniques ....Self-supervised feature learning for rapid processing of marine imagery. Fast and reliable quantitative estimates of marine environmental health are needed for scientific studies, design and management of protected areas, and regulatory compliance of industrial activity in the ocean. Australia is collecting seafloor images at increasing rates but expert annotations are not keeping up, meaning that typical machine learning approaches struggle. This project will develop self-supervised techniques that use large amounts of unlabeled data to enhance performance. Our design takes advantage of additional information available for marine imagery such as geolocation and remote sensing context. We will explore how these representations can guide additional sampling and improve performance in classification tasks.Read moreRead less