Early Career Industry Fellowships - Grant ID: IE230100380
Funder
Australian Research Council
Funding Amount
$390,574.00
Summary
Enhancing comprehension of forensic science in the justice system. Failures to effectively communicate the accuracy and reliability of forensic evidence to courts can lead to unreliable convictions and miscarriages of justice. This project aims to understand how best to distil complex information about error and uncertainty in forensic expert opinion evidence for enhanced comprehension of forensic science in the justice system. Outcomes include evidence-based strategies for communicating error a ....Enhancing comprehension of forensic science in the justice system. Failures to effectively communicate the accuracy and reliability of forensic evidence to courts can lead to unreliable convictions and miscarriages of justice. This project aims to understand how best to distil complex information about error and uncertainty in forensic expert opinion evidence for enhanced comprehension of forensic science in the justice system. Outcomes include evidence-based strategies for communicating error and uncertainty in forensic science and an accessible online dashboard for visualising known error rates in forensic disciplines. The knowledge gained from the project will help forensic experts to calibrate how they present their conclusions to courts for improved comprehension and evaluation of forensic evidence.Read moreRead less
The architecture of Australia's Muslim pioneers. This project will survey the remnant architecture of Australia's Muslim cameleers who played a vital role in the discovery, exploration and settlement of Australia. The project will generate three-dimensional visualisations of these settlements and academic publications in addition to material for the public education programs operated by the South Australian Museum.
Structured barrier and penalty functions in infinite dimensional optimisation and analysis. Very large scale tightly-constrained optimisation problems are ubiquitous and include water management, traffic flow, and imaging at telescopes and hospitals. Massively parallel computers can solve such problems and provide physically realisable solution only if subtle design issues are mastered. Resolving such issues is the goal of this project.
ARC Research Network in Enterprise Information Infrastructure. EII targets consolidated research towards the comprehensive development & establishment of advanced information infrastructures. Its prime purpose is to provide a forum for intellectual exchange by diverse yet complementary research groups, to address the fundamental research problems faced by scientific & business communities when dealing with deployment of information technology to globally distributed, and data intensive environme ....ARC Research Network in Enterprise Information Infrastructure. EII targets consolidated research towards the comprehensive development & establishment of advanced information infrastructures. Its prime purpose is to provide a forum for intellectual exchange by diverse yet complementary research groups, to address the fundamental research problems faced by scientific & business communities when dealing with deployment of information technology to globally distributed, and data intensive environments. EII will address 3 tightly coupled research themes: Ability to interoperate across existing heterogenous platforms & applications; Efficient processing of very large data sets; Technology adoption & impact. Generic results will be applicable to e-science and large business information systems installations.Read moreRead less
Where do inductive biases come from? A Bayesian investigation. This project aims to investigate the origin of our thinking and learning biases using state-of-the-art mathematical models and sophisticated experimental designs. Expected outcomes include bridging the gap between human and machine learning by pairing mathematical modelling with experimental work, forming a necessary step toward the development of machine systems that can reason like people do. This will provide significant benefits ....Where do inductive biases come from? A Bayesian investigation. This project aims to investigate the origin of our thinking and learning biases using state-of-the-art mathematical models and sophisticated experimental designs. Expected outcomes include bridging the gap between human and machine learning by pairing mathematical modelling with experimental work, forming a necessary step toward the development of machine systems that can reason like people do. This will provide significant benefits such as understanding how people operate so effectively in real environments, when even the most powerful computers struggle to handle the complexities of everyday learning problems.Read moreRead less
Improving the diagnosticity of eyewitness memory choices. Eyewitness identification error is common and costly. This project aims to improve the quality of information provided by eyewitnesses, and the ability of police officers and triers of fact (e.g., juries, judges) to evaluate this information. Laboratory investigations will determine how best to test memory and confidence to achieve this aim. A new class of cognitive models will provide a unified account of response accuracy, response time ....Improving the diagnosticity of eyewitness memory choices. Eyewitness identification error is common and costly. This project aims to improve the quality of information provided by eyewitnesses, and the ability of police officers and triers of fact (e.g., juries, judges) to evaluate this information. Laboratory investigations will determine how best to test memory and confidence to achieve this aim. A new class of cognitive models will provide a unified account of response accuracy, response time, and confidence, suitable for application to computerized testing scenarios. The models and testing methods validated in the laboratory will be refined for application in eyewitness memory settings, facilitating better evaluation of identification evidence, and potentially reducing wrongful convictions.Read moreRead less
Data-driven water quality treatment management decision support system. Data-driven water quality treatment management decision support system. This project aims to develop a robust decision support system to predict manganese and the character and concentration of dissolved organic matter in drinking water reservoirs, using intelligent algorithms and data collected through remote autonomous instrumentation. These predicted water quality parameters could be used as model input variables to provi ....Data-driven water quality treatment management decision support system. Data-driven water quality treatment management decision support system. This project aims to develop a robust decision support system to predict manganese and the character and concentration of dissolved organic matter in drinking water reservoirs, using intelligent algorithms and data collected through remote autonomous instrumentation. These predicted water quality parameters could be used as model input variables to provide real-time decisions for plant operators on the required treatment regime for incoming raw water, and advise them on the optimal reservoir offtake depth. This will potentially minimise treatment costs and health risks for consumers. The ultimate goal is to significantly enhance current water supply management practices.Read moreRead less
Classification methods for providing personalised and class decisions. This project provides a novel approach to the clustering of multivariate samples on entities in a class that automatically matches the sample clusters across the entities, allowing for inter-sample variation between the samples in a class. The project aims to develop a widely applicable, mixture-model-based framework for the simultaneous clustering of multivariate samples with inter-sample variation in a class and for the mat ....Classification methods for providing personalised and class decisions. This project provides a novel approach to the clustering of multivariate samples on entities in a class that automatically matches the sample clusters across the entities, allowing for inter-sample variation between the samples in a class. The project aims to develop a widely applicable, mixture-model-based framework for the simultaneous clustering of multivariate samples with inter-sample variation in a class and for the matching of the clusters across the entities in the class. The project will use a statistical approach to automatically match the clusters, since the overall mixture model provides a template for the class. It will provide a basis for discriminating between different classes in addition to the identification of atypical data points within a sample and of anomalous samples within a class. Key applications include biological image analysis and the analysis of data in flow cytometry which is one of the fundamental research tools for the life scientist.Read moreRead less
Campus: Building Modern Australian Universities. This project plans to examine the post-World War Two evolution of the Australian university campus. Modern campuses created opportunities for the realisation of innovative solutions in urban planning, architecture and landscape. The project plans to reveal the physical impacts of political, institutional, social and cultural demands through comparative thematic investigation, digital visualisation and detailed case studies. Foregrounding landscape ....Campus: Building Modern Australian Universities. This project plans to examine the post-World War Two evolution of the Australian university campus. Modern campuses created opportunities for the realisation of innovative solutions in urban planning, architecture and landscape. The project plans to reveal the physical impacts of political, institutional, social and cultural demands through comparative thematic investigation, digital visualisation and detailed case studies. Foregrounding landscape and site, the project aims to establish new historical knowledge, identify campuses as catalysts for urban thinking, and demonstrate strategies for their conservation and adaptation to meet future needs in the tertiary sector.Read moreRead less