Attention please! Selective attention and human associative learning. Selective attention allows us to pick useful pieces of information out of the mass of stimulation that we're faced with every moment. This project investigates how what we've previously learnt about the significance of events influences whether we'll pick them out as useful in future, and how this might be impaired by old age or mental disorder.
Learning the complexity of scientific knowledge about climate change with computer modelling and visualization technologies. This project provides benefits to the national priorities of a environmentally sustainable Australia; and frontier technologies for building and transforming Australian industries. The project helpins students in Australia more deeply understand the sciences that underlie environmental sustainability. Learning with modelling and visualization technologies will help student ....Learning the complexity of scientific knowledge about climate change with computer modelling and visualization technologies. This project provides benefits to the national priorities of a environmentally sustainable Australia; and frontier technologies for building and transforming Australian industries. The project helpins students in Australia more deeply understand the sciences that underlie environmental sustainability. Learning with modelling and visualization technologies will help students learn important scientific knowledge and prepare them for the use of frontier technologies that are becoming infused into the practices of scientists and professionals in many fields. This project also directly contributes to the national Digital Education Revolution initiative.Read moreRead less
Incremental syntactic parsing and coreference resolution. As computers become smaller, keyboards and screens become increasingly impractical. We'd like to be able to talk to our computers, but they'd have to understand what we say. This project will develop a computational model that tracks which things are talked about and identifies 'who did what to whom' in text or speech.
Computational models of synergies in human language acquisition. How do children learn language? Do they first learn to recognise words and then associate words with meanings, or do they use the meanings to figure out what the words are, or do they do both at the same time, and if so, how? This project will investigate questions like these using advanced computational models of the way children learn from their environment.
Discovery Early Career Researcher Award - Grant ID: DE120100898
Funder
Australian Research Council
Funding Amount
$375,000.00
Summary
The brain that adapts itself - flexible processing in an ever-changing world. To cope with the changing world around us, our brains must constantly adapt themselves, reconfiguring an incredibly complex system to produce flexible behaviour. This project will develop innovative brain imaging techniques and use them to examine this process in vision, fundamental for understanding the human brain, and advancing neuroscience in Australia.
Solving the inert knowledge problem. A central goal of education is for students to transfer what they learn to new contexts or problems. Indeed, expert reasoning is often characterised by seeing the deep structural commonalities across seemingly disparate situations. However, the knowledge students acquire is notoriously inert, tied to the specifics of the learning examples. This project aims to move towards solving 'the inert knowledge problem' by investigating how humans learn concepts define ....Solving the inert knowledge problem. A central goal of education is for students to transfer what they learn to new contexts or problems. Indeed, expert reasoning is often characterised by seeing the deep structural commonalities across seemingly disparate situations. However, the knowledge students acquire is notoriously inert, tied to the specifics of the learning examples. This project aims to move towards solving 'the inert knowledge problem' by investigating how humans learn concepts defined by abstract relational structure, and by designing educational applications that enhance the use of relational learning mechanisms in students with a wide range of cognitive abilities.Read moreRead less
Making sense of the world: how does the brain process task-relevant information? Contributing to a global effort to understand the human brain, this project will develop and use innovative brain imaging techniques to ask how our brains make sense of the world. This project establishes collaboration with a world renowned research centre in Cambridge, UK, and will be fundamental for advancing basic science in Australia.
How is information organised in the mind? Learning structured mental representations from data. One of the biggest questions in psychology is to understand the principles that the mind uses to organise information. This project is both a search for these underlying psychological laws, and an attempt to develop new statistical technologies and mathematical tools that can be used to organise information in applied settings.
Developing a personalised Music Affect Recommender System. The project aims to develop a personalised music recommender system using perceived tone quality, affect and liking. Recommender systems using prior verbal annotations and ratings are common (Amazon) but inappropriate for less popular music by unfamiliar artists, which lacks social use data. The project intends to build on work into perception of musical affect and its relation to loudness and tone quality; and the automation of the orga ....Developing a personalised Music Affect Recommender System. The project aims to develop a personalised music recommender system using perceived tone quality, affect and liking. Recommender systems using prior verbal annotations and ratings are common (Amazon) but inappropriate for less popular music by unfamiliar artists, which lacks social use data. The project intends to build on work into perception of musical affect and its relation to loudness and tone quality; and the automation of the organisation of digital libraries both by labels and acoustic content. Developing this, the project seeks to create a model that gives recommendations which accounts for an individual's preferences based on acoustic content, affect and liking. The system will be designed to update rapidly and to encourage exploration of familiar and unfamiliar music.Read moreRead less
The dog that didn't bark: a Bayesian account of reasoning from censored data. This project aims to develop and test a new computational theory of inductive reasoning. Inductive reasoning involves extending knowledge from known to novel instances, and is a central component of intelligent behaviour. This project will address the cognitive mechanisms that allow people to draw inferences based on both observed and censored evidence. The project intends to test the model through an extensive program ....The dog that didn't bark: a Bayesian account of reasoning from censored data. This project aims to develop and test a new computational theory of inductive reasoning. Inductive reasoning involves extending knowledge from known to novel instances, and is a central component of intelligent behaviour. This project will address the cognitive mechanisms that allow people to draw inferences based on both observed and censored evidence. The project intends to test the model through an extensive program of experimental investigation and computational modelling. The anticipated benefits include an enhanced understanding of human inference, especially in domains such as the evaluation of forensic or financial evidence, where data censoring is common.Read moreRead less