Natural form, aesthetics and the human brain. This project aims to study how the brain represents the emotion of aesthetic experience. This project will establish the characteristics of flowers and floral design that govern their appeal using large scale web based data collection, and identify the neural representation of floral beauty using integrative data analysis. Outcomes of the project are expected to help flower growers and designers with product planning, supporting industry sustainabili ....Natural form, aesthetics and the human brain. This project aims to study how the brain represents the emotion of aesthetic experience. This project will establish the characteristics of flowers and floral design that govern their appeal using large scale web based data collection, and identify the neural representation of floral beauty using integrative data analysis. Outcomes of the project are expected to help flower growers and designers with product planning, supporting industry sustainability. The project will also establish how the brain generates positive experience in response to our visual environment, promoting well-being by enabling informed visual design decisions.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE200101468
Funder
Australian Research Council
Funding Amount
$413,614.00
Summary
Context matters: from sensory processing to decision making. Contextual modulation refers to prominent changes in the processing of information in brain and perception caused by interactions across space and time. Over the past two decades, an enormous amount of work has shown that spatial contextual effects occur throughout the sensory processing hierarchy. However, there has been little work examining how temporal context effects affect information processing and operate for high-level attribu ....Context matters: from sensory processing to decision making. Contextual modulation refers to prominent changes in the processing of information in brain and perception caused by interactions across space and time. Over the past two decades, an enormous amount of work has shown that spatial contextual effects occur throughout the sensory processing hierarchy. However, there has been little work examining how temporal context effects affect information processing and operate for high-level attributes of stimuli as well as interactions of self and environment. The project aims to fill this gap to further understand the nature and mechanisms of temporal contextual modulation on sensory information processing, perception, perceptual judgement and decision making at cellular, circuit and cognitive levels.Read moreRead less
Creating perceptual experts in Australia's policing and security agencies. This project aims to create the next generation of experts in Australia’s policing and national security agencies, by improving crime scene evidence interpretation. Agencies are under pressure to develop more rigorous training practices that go beyond mere intuition and tradition. This project will use a novel approach that directs learning toward the most diagnostic perceptual cues. Expected outcomes include a solid empi ....Creating perceptual experts in Australia's policing and security agencies. This project aims to create the next generation of experts in Australia’s policing and national security agencies, by improving crime scene evidence interpretation. Agencies are under pressure to develop more rigorous training practices that go beyond mere intuition and tradition. This project will use a novel approach that directs learning toward the most diagnostic perceptual cues. Expected outcomes include a solid empirical basis for national training programs designed to create experts that are accurate, reliable, and continuously improving. Improving the training of experts will ensure the integrity of forensics as evidentiary tools available to police, lead to more reliable courtroom convictions and help safeguard Australia from terrorism and crime.Read moreRead less
Efficient multi-view video coding with cuboids and base anchored models. This project aims to address current deficiencies in multi-view video coding technology to achieve the ultra-compression efficiency demanded by increasing display resolutions and synchronised viewpoints. The project expects to generate new knowledge, by moving from the current pixel-centric approach to methods that concentrate information common to many view-frames. The project is expected to improve compression of audio-vi ....Efficient multi-view video coding with cuboids and base anchored models. This project aims to address current deficiencies in multi-view video coding technology to achieve the ultra-compression efficiency demanded by increasing display resolutions and synchronised viewpoints. The project expects to generate new knowledge, by moving from the current pixel-centric approach to methods that concentrate information common to many view-frames. The project is expected to improve compression of audio-visual services that are of great interest to international standards bodies and industry, while facilitating free interaction and augmented reality. This project will provide significant benefits to broadcast, entertainment, surveillance and health industries and position Australia as a world leader in this field.Read moreRead less
Searching for near-exact protein models. This project aims to develop novel and efficient heuristic-based algorithms leading to near accurate protein tertiary structure models. Knowledge about protein structures is fundamental to our understanding of living systems. The progress on experimental determination of these structures has been extremely limited and remains an open challenge in molecular biology. Computational prediction of protein structures from sequences is emerging as a promising ap ....Searching for near-exact protein models. This project aims to develop novel and efficient heuristic-based algorithms leading to near accurate protein tertiary structure models. Knowledge about protein structures is fundamental to our understanding of living systems. The progress on experimental determination of these structures has been extremely limited and remains an open challenge in molecular biology. Computational prediction of protein structures from sequences is emerging as a promising approach, but its accuracy is far from satisfactory. The software systems developed in this project will be used in structural identification of target proteins in drug design. This will make drug design process more efficient, saving time and cost, potentially saving lives.Read moreRead less
Low-cost Sensing Methods and Hybrid Learning Models. This project aims to revolutionise the theory and practice of sensing and monitoring by developing novel Artificial Intelligence and Internet of Things technologies. This project expects to generate new knowledge in the area of Artificial Intelligence of Things by combining sensing, machine learning, and big data analytics. Expected outcomes of this project include novel low-cost sensing methods and new hybrid machine learning models for predi ....Low-cost Sensing Methods and Hybrid Learning Models. This project aims to revolutionise the theory and practice of sensing and monitoring by developing novel Artificial Intelligence and Internet of Things technologies. This project expects to generate new knowledge in the area of Artificial Intelligence of Things by combining sensing, machine learning, and big data analytics. Expected outcomes of this project include novel low-cost sensing methods and new hybrid machine learning models for predictive sensory data analytics. This should provide significant benefits, such as substantially reduced operating and service costs and improved accuracy for real-time monitoring in the fields where cheap-to-implement and easy-to-service monitoring systems over large geographical areas are imperative.Read moreRead less
An intelligent machine modelling assistant for combinatorial optimisation. This project aims to discover key fundamental technologies for automating assistance to non-expert users in the formulation of mathematical models. Through automating the modelling of combinatorial optimization problems, this research will generate new knowledge to address the fundamental challenges of automatic mathematical modelling. This intelligent assistant will enable synthesis of new mathematical models through th ....An intelligent machine modelling assistant for combinatorial optimisation. This project aims to discover key fundamental technologies for automating assistance to non-expert users in the formulation of mathematical models. Through automating the modelling of combinatorial optimization problems, this research will generate new knowledge to address the fundamental challenges of automatic mathematical modelling. This intelligent assistant will enable synthesis of new mathematical models through the utilisation of pioneering natural language processing components and novel custom-made machine-readable knowledge bases. The outcome of this research will broaden access to high-quality models by non-expert workforce and alleviate the shortage of expert mathematicians, bringing significant social and economic benefits.Read moreRead less
Human Scheduling of Perceptual Tasks. This project aims to develop a novel approach for synthesising how people prioritise information with theories of attention and decision making. Characterising inefficient scheduling in the tradeoff between the difficulty and the cost/benefit of different subtasks will allow the development of a formal computional model that generalises statistical models of rank order data to a theory of the timing of scheduling decisions and task completions. Outcomes incl ....Human Scheduling of Perceptual Tasks. This project aims to develop a novel approach for synthesising how people prioritise information with theories of attention and decision making. Characterising inefficient scheduling in the tradeoff between the difficulty and the cost/benefit of different subtasks will allow the development of a formal computional model that generalises statistical models of rank order data to a theory of the timing of scheduling decisions and task completions. Outcomes include benchmark data from a novel paradigm for studying perceptual decisions and behavior and a model which can explain and predict human scheduling. This project aims to benefit industry by allowing for the simulation of information prioritisation by human agents in complex environments.Read moreRead less
Personalised Learning for Per-pixel Prediction Tasks in Image Analysis. AI-assisted image segmentation & synthesis are very challenging and usually require pixel-level labelling (per-pixel prediction) that is costly to obtain. The small amount of labels makes it difficult to train an “optimal” unified model for varied data as conventional methods did. This project aims to develop a new paradigm “personalised learning” to tackle this problem, where each image could be dealt with a model tailored ....Personalised Learning for Per-pixel Prediction Tasks in Image Analysis. AI-assisted image segmentation & synthesis are very challenging and usually require pixel-level labelling (per-pixel prediction) that is costly to obtain. The small amount of labels makes it difficult to train an “optimal” unified model for varied data as conventional methods did. This project aims to develop a new paradigm “personalised learning” to tackle this problem, where each image could be dealt with a model tailored to individual characteristics. The success of this project could significantly advance the fundamental research in image analysis. Expected outcomes include new knowledge and algorithms for image analysis, which could benefit fields like biology and archaeology, where labeled images are hard to attain and scarce.Read moreRead less