From insects to robots: how brains make predictions and ignore distractions. This project aims to address fundamental questions in neuroscience and to integrate this biological understanding with the development of leading-edge robotics. Whether a human catching a ball or a dragonfly feeding in a swarm, brains have the remarkable ability to predict the future location of moving targets. The brain predicts in the presence of distractions and even if the target disappears, for example, when hidden ....From insects to robots: how brains make predictions and ignore distractions. This project aims to address fundamental questions in neuroscience and to integrate this biological understanding with the development of leading-edge robotics. Whether a human catching a ball or a dragonfly feeding in a swarm, brains have the remarkable ability to predict the future location of moving targets. The brain predicts in the presence of distractions and even if the target disappears, for example, when hidden behind another object. This project will investigate how brains use both environmental and internal information to select a target and predict its future location. By implementing bio-inspired computations in hardware, this project aims to provide significant benefits such as improving autonomous systems for defence, health and transportation.Read moreRead less
Deep visual understanding: learning to see in an unruly world. Deep Learning has achieved incredible success at an astonishing variety of Computer Vision tasks recently. This project aims to convey this success into the challenging domain of high-level image-based reasoning. It will extend deep learning to achieve flexible semantic reasoning about the content of images based on information gleaned from the huge volumes of data available on the Internet. The project expects to overcome one of the ....Deep visual understanding: learning to see in an unruly world. Deep Learning has achieved incredible success at an astonishing variety of Computer Vision tasks recently. This project aims to convey this success into the challenging domain of high-level image-based reasoning. It will extend deep learning to achieve flexible semantic reasoning about the content of images based on information gleaned from the huge volumes of data available on the Internet. The project expects to overcome one of the primary limitations of deep learning and will greatly increase its practical application to a range of industrial, cultural or health settings.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE190100539
Funder
Australian Research Council
Funding Amount
$408,000.00
Summary
Towards conversational vision-based Artificial Intelligence. This project aims to develop a novel learning framework, Vision-Ask-Answer-Act (V3A). This framework will allow a machine to perform a sequence of actions via a conversation with human users, based on intricate processing of not just visual input, but human-computer verbal exchanges. Artificial intelligence has great potential as a tool for economic productivity and daily tasks. Applications in cars and assistant robots, still in their ....Towards conversational vision-based Artificial Intelligence. This project aims to develop a novel learning framework, Vision-Ask-Answer-Act (V3A). This framework will allow a machine to perform a sequence of actions via a conversation with human users, based on intricate processing of not just visual input, but human-computer verbal exchanges. Artificial intelligence has great potential as a tool for economic productivity and daily tasks. Applications in cars and assistant robots, still in their early days, typically require significant expertise to use effectively. The outcomes of this project will push the boundary of vision-language research to produce a conversational intelligent agent that can be easily used in common situations across industry, transport, the medical sector, and at home.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
Action selection in insects: how a microbrain knows what to do. Identifying what to do demands integrating sensory information with our current physiological state and memory of past experience to select the best possible action. This is the action selection problem. Our project aims to discover how tiny insect brains solve this fundamental problem. The project combines neural recordings from animals exploring virtual reality, behavioural analyses and computational modelling. The expected outco ....Action selection in insects: how a microbrain knows what to do. Identifying what to do demands integrating sensory information with our current physiological state and memory of past experience to select the best possible action. This is the action selection problem. Our project aims to discover how tiny insect brains solve this fundamental problem. The project combines neural recordings from animals exploring virtual reality, behavioural analyses and computational modelling. The expected outcome is a new understanding of the brain as an effective behavioural control system. This will benefit systems and comparative neuroscience. Our findings may also inspire solutions for robotic systems that must operate autonomously in remote and challenging environments such as disaster relief or exploration.Read moreRead less
Making Meta-learning Generalised . This project aims to develop novel machine learning techniques, termed generalised meta-learning, to make machines better utilise past experience to solve new tasks with few data. It expects to reduce the undesirable dependence of current machine learning on labelled data and significantly expand its application scope. Expected outcomes of the project consist of new theoretical results on meta-learning and a set of innovative algorithms that can support the bui ....Making Meta-learning Generalised . This project aims to develop novel machine learning techniques, termed generalised meta-learning, to make machines better utilise past experience to solve new tasks with few data. It expects to reduce the undesirable dependence of current machine learning on labelled data and significantly expand its application scope. Expected outcomes of the project consist of new theoretical results on meta-learning and a set of innovative algorithms that can support the building of next generation of computer vision systems to work in open and dynamic environments. This should be able to produce solid benefits to the science, society, and economy of Australian via the application of these advanced intelligent systems.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE220100265
Funder
Australian Research Council
Funding Amount
$417,000.00
Summary
A closed-loop human–agent learning framework to enhance decision making. This project aims to design a foundational human–agent learning framework to augment the decision making process, using reinforcement and closed-loop mechanisms to enable symbiosis between a human and an artificial-intelligence agent. It envisages significant new technologies to promote controllability and efficient and safe exploration of an environment for decision actions – drastically boosting learning effectiveness and ....A closed-loop human–agent learning framework to enhance decision making. This project aims to design a foundational human–agent learning framework to augment the decision making process, using reinforcement and closed-loop mechanisms to enable symbiosis between a human and an artificial-intelligence agent. It envisages significant new technologies to promote controllability and efficient and safe exploration of an environment for decision actions – drastically boosting learning effectiveness and interpretability in decision making. Expected outcomes will benefit national cybersecurity by improving our understanding of vulnerabilities and threats involving decision actions, and by ensuring that human feedback and evaluations can help prevent catastrophic events in explorations of dynamic and complex environments.Read moreRead less
Target detection: neural networks, behaviour and biomimetic applications. This project aims to understand the neural and behavioural mechanisms that allow insects to efficiently detect moving targets in visual clutter, despite being equipped with small brains and low-resolution eyes. The project is expected to generate fundamental knowledge using a unique combination of quantitative behaviour, neurophysiology, pharmacological intervention and biomimetic modelling. Expected outcomes include an in ....Target detection: neural networks, behaviour and biomimetic applications. This project aims to understand the neural and behavioural mechanisms that allow insects to efficiently detect moving targets in visual clutter, despite being equipped with small brains and low-resolution eyes. The project is expected to generate fundamental knowledge using a unique combination of quantitative behaviour, neurophysiology, pharmacological intervention and biomimetic modelling. Expected outcomes include an increased understanding of neural mechanisms underlying sensory selectivity, the development of novel techniques, and enhanced capacity for interdisciplinary collaborations. The project will provide significant knowledge as the developed biomimetic algorithms should be applicable for increased performance in drones or other unmanned vehicles.Read moreRead less
Things don’t always go better with Coke. This project aims to test whether soft drink use is governed partly by automatic processes (cognitive biases) that operate largely outside of conscious control. In so doing, the project expects to generate a new conceptual understanding of the mechanisms that drive the overconsumption of soft drinks. Expected outcomes include theoretical innovation, new research methodologies, and accessible cost-effective technologies for reducing excessive sugar intake ....Things don’t always go better with Coke. This project aims to test whether soft drink use is governed partly by automatic processes (cognitive biases) that operate largely outside of conscious control. In so doing, the project expects to generate a new conceptual understanding of the mechanisms that drive the overconsumption of soft drinks. Expected outcomes include theoretical innovation, new research methodologies, and accessible cost-effective technologies for reducing excessive sugar intake from soft drinks, in line with recent World Health Organization guidelines. These outcomes will contribute to combatting obesity and tooth decay.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE150101108
Funder
Australian Research Council
Funding Amount
$352,000.00
Summary
The ups and downs of visuospatial attention. The brain has a remarkable capacity to provide a coherent experience of the world by seamlessly integrating sights and sounds from different locations. It is only after brain damage, or when faced with a high attentional load, that our limitations become apparent. The project aims to investigate these limitations by determining how spatial location influences attention in relation to distractibility, cross-modal input and emotionality. Eye tracking an ....The ups and downs of visuospatial attention. The brain has a remarkable capacity to provide a coherent experience of the world by seamlessly integrating sights and sounds from different locations. It is only after brain damage, or when faced with a high attentional load, that our limitations become apparent. The project aims to investigate these limitations by determining how spatial location influences attention in relation to distractibility, cross-modal input and emotionality. Eye tracking and physiological measures of arousal will be combined with traditional cognitive measures to provide a deeper understanding of spatial attention. This project aims to improve attentional models and develop innovative strategies to increase safety by decreasing inattention and distraction.Read moreRead less