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.Read moreRead less
Visual methods for advanced automation of underwater manipulation. This project will increase the autonomy of underwater robotic systems engaged in intervention and inspection tasks. Such activities are essential for the operation of subsea robotic systems used in offshore industries, scientific exploration and defence. Our approach will improve perception and situational awareness through the principled fusion of multiple navigation and camera sensors. We will use this improved scene understand ....Visual methods for advanced automation of underwater manipulation. This project will increase the autonomy of underwater robotic systems engaged in intervention and inspection tasks. Such activities are essential for the operation of subsea robotic systems used in offshore industries, scientific exploration and defence. Our approach will improve perception and situational awareness through the principled fusion of multiple navigation and camera sensors. We will use this improved scene understanding to effectively plan the motion of vehicles and manipulators through larger and more complex workspaces, enabling semi-supervised and autonomous task execution. Our project will demonstrate these capabilities in real-world deployments relevant to industry and marine science.Read moreRead less
Human models for accelerated robot learning and human-robot interaction. This project aims to develop novel approaches to teach robots to proficiently interact with humans in a safe and low-cost manner. To achieve this aim, this project will develop novel models from which various human behaviours can be generated and used to train human-robot interaction policies in simulation. Expected outcomes of this project include new computational models of human behaviour built using cognitive science th ....Human models for accelerated robot learning and human-robot interaction. This project aims to develop novel approaches to teach robots to proficiently interact with humans in a safe and low-cost manner. To achieve this aim, this project will develop novel models from which various human behaviours can be generated and used to train human-robot interaction policies in simulation. Expected outcomes of this project include new computational models of human behaviour built using cognitive science theories and limited data and new training schemes for robot learning in simulation. By training robots in simulation with accurate human models, this research will enable fast and safe robot training to support the deployment and adoption of robots in human contexts such as healthcare facilities, homes, and workplaces.Read moreRead less
Small Scalable Natural Language Models using Explicit Memory. Deep neural networks have had spectacular success in natural language processing, seeing wide-spread deployment as part of automatic assistant devices in homes and cars, and across many valuable industries including finance, medicine and law. Fueling this success is the use of ever larger models, with exponentially increasing training resources, accompanying hardware and energy demands. This project aims to develop more compact models ....Small Scalable Natural Language Models using Explicit Memory. Deep neural networks have had spectacular success in natural language processing, seeing wide-spread deployment as part of automatic assistant devices in homes and cars, and across many valuable industries including finance, medicine and law. Fueling this success is the use of ever larger models, with exponentially increasing training resources, accompanying hardware and energy demands. This project aims to develop more compact models, based on the incorporation of an explicit searchable memory, which will dramatically reduce model size, hardware requirements and energy usage. This will make modern natural language processing more accessible, while also providing greater flexibility, allowing for more adaptable and portable technologies.Read moreRead less
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.Read moreRead less
Automatic detection and modelling of acoustic markers of speech timing. This project aims to create new automatic sensing, analysis and assessment of cognitive, affective, mental and physical state from voice for mobile and computing devices. This project expects to generate new understanding of the effects of these states on detailed timing indicators of speech motor control, and new signal processing and machine learning methods that best exploit it. Expected outcomes from this project include ....Automatic detection and modelling of acoustic markers of speech timing. This project aims to create new automatic sensing, analysis and assessment of cognitive, affective, mental and physical state from voice for mobile and computing devices. This project expects to generate new understanding of the effects of these states on detailed timing indicators of speech motor control, and new signal processing and machine learning methods that best exploit it. Expected outcomes from this project include a new and accurate deep neural network framework for learning, analysing and detecting human states from speech automatically using articulatory timing markers. This should provide significant benefits, such as individually-tailored, frequent and low-cost automatic detection, monitoring and analytics for adverse states.Read moreRead less
Interactions of Human and Machine Intelligence in Modern Economic Systems. Much of modern economic systems are driven by machine-machine and machine-human interactions that happens rapidly at large scale. But such interactions are often opaque and can have negative or catastrophic consequences, such as market plunges with no apparent economic reasons in financial trading, content recommendations that promote extremism, algorithms in gig economy leading to worker exploitation and wasted resources ....Interactions of Human and Machine Intelligence in Modern Economic Systems. Much of modern economic systems are driven by machine-machine and machine-human interactions that happens rapidly at large scale. But such interactions are often opaque and can have negative or catastrophic consequences, such as market plunges with no apparent economic reasons in financial trading, content recommendations that promote extremism, algorithms in gig economy leading to worker exploitation and wasted resources. This project aims for new theoretical results and algorithms at the intersection computational economics, game theory, and dynamical systems, that establish conditions under which the economic systems are stable, propose mechanisms that make the interactions more fair, transparent and aligned with human values.Read moreRead less
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.Read moreRead less
Advanced Machine Learning with Bilevel Optimization. There is an urgent need to develop a new machine learning (ML) paradigm that can overcome data-privacy and model-size constraints in real-world applications. This project aims to develop an advanced paradigm of ML with bilevel optimisation, called bilevel ML. A theoretically-guaranteed fast approximate solver and a new fuzzy bilevel learning framework will be developed to achieve the aim in complex situations; a methodology to transfer knowled ....Advanced Machine Learning with Bilevel Optimization. There is an urgent need to develop a new machine learning (ML) paradigm that can overcome data-privacy and model-size constraints in real-world applications. This project aims to develop an advanced paradigm of ML with bilevel optimisation, called bilevel ML. A theoretically-guaranteed fast approximate solver and a new fuzzy bilevel learning framework will be developed to achieve the aim in complex situations; a methodology to transfer knowledge and an approach to fast-adapt bilevel optimization solutions when required computing resources change. The anticipated outcomes should significantly improve the reliability of ML with benefits for safety learning and computing resource optimisation in ML-based data analytics.Read moreRead less
Intelligent Robotics for Pharmaceutical Formulation Development. This project aims to transform the labour and time-intensive process of drug formulation development by optimising the process workflow, through collaboration between biochemists and the proposed intelligent and scalable robotic system. This project expects to enable the robot to leverage the expert knowledge of the biochemists while automating rote tasks. The expected outcome of this project is an intelligent robot that can collab ....Intelligent Robotics for Pharmaceutical Formulation Development. This project aims to transform the labour and time-intensive process of drug formulation development by optimising the process workflow, through collaboration between biochemists and the proposed intelligent and scalable robotic system. This project expects to enable the robot to leverage the expert knowledge of the biochemists while automating rote tasks. The expected outcome of this project is an intelligent robot that can collaborate with human coworkers to accelerate drug formulation. This should provide significant benefits by lowering drug costs and the development time of new drugs. Read moreRead less