Problematic interactions between autistic adults and the justice system. This project aims to highlight how autistic adults may fall foul of the law due to a diminished ability to recognise subtle cues in social interactions that should warn of unfolding criminal activity or deteriorating relationships with justice system personnel. Autism Spectrum Disorder has unique characteristics that may lead to unwitting involvement in crime and problematic interactions with the justice system. This projec ....Problematic interactions between autistic adults and the justice system. This project aims to highlight how autistic adults may fall foul of the law due to a diminished ability to recognise subtle cues in social interactions that should warn of unfolding criminal activity or deteriorating relationships with justice system personnel. Autism Spectrum Disorder has unique characteristics that may lead to unwitting involvement in crime and problematic interactions with the justice system. This project expects to unveil innovative research paradigms, establish a knowledge base for police and the courts, and assist in developing guidelines for remediating misunderstandings that contribute to problematic interactions with the justice system.Read moreRead less
Inference for Hawkes processes with challenging data. The Hawkes processes are statistical models for the analysis of high-impact event sequences, such as bushfires, earthquakes, infectious diseases, and cyber attacks. When the times and/or marks are missing for some events or when the data is otherwise incomplete, it is challenging to fit these models and perform diagnostic checks on the fitted models. This project aims to develop novel statistical methods to fit these models in the presence of ....Inference for Hawkes processes with challenging data. The Hawkes processes are statistical models for the analysis of high-impact event sequences, such as bushfires, earthquakes, infectious diseases, and cyber attacks. When the times and/or marks are missing for some events or when the data is otherwise incomplete, it is challenging to fit these models and perform diagnostic checks on the fitted models. This project aims to develop novel statistical methods to fit these models in the presence of incomplete data and to check the goodness-of-fit of the fitted models. The expected outcomes include publications documenting these methods and software packages implementing them. The primary benefits include the advancement of statistical methodology and the training of junior research personnel. Read moreRead less
Fast approximate inference methods: new algorithms, applications and theory. This project aims to develop new algorithms and theory for fast approximate inference and lay down infrastructure to aid future extensions. Fast approximate inference methods are a principled and extensible means of fitting large and complex statistical models to big data sets. They come into their own in applications where speed is paramount and traditional approaches are not feasible. The project aims to lead to prac ....Fast approximate inference methods: new algorithms, applications and theory. This project aims to develop new algorithms and theory for fast approximate inference and lay down infrastructure to aid future extensions. Fast approximate inference methods are a principled and extensible means of fitting large and complex statistical models to big data sets. They come into their own in applications where speed is paramount and traditional approaches are not feasible. The project aims to lead to practical outcomes from better business decision-making for insurance data warehouses, to improved medical imaging technology.Read moreRead less
Scalable and Robust Bayesian Inference for Implicit Statistical Models. This project aims to develop the next generation of efficient methods for fitting complex simulation-based statistical models to data. Practitioners and scientists are interested in such implicit models to enable discoveries, produce accurate predictions and inform decisions under uncertainty. However, the associated computational cost has restricted researchers to implicit models that must have a small number of parameters ....Scalable and Robust Bayesian Inference for Implicit Statistical Models. This project aims to develop the next generation of efficient methods for fitting complex simulation-based statistical models to data. Practitioners and scientists are interested in such implicit models to enable discoveries, produce accurate predictions and inform decisions under uncertainty. However, the associated computational cost has restricted researchers to implicit models that must have a small number of parameters and be well specified, impeding scientific progress. This project will develop new computational methods and algorithms for implicit models that scale to high dimensions and are robust to misspecification. Benefits will arise from the more routine use of implicit models in epidemiology, biology, ecology and other fields.Read moreRead less
Advances in Sequential Monte Carlo Methods for Complex Bayesian Models. This project aims to develop efficient statistical algorithms for parameter estimation of complex stochastic models that currently cannot be handled. Parameter estimation is an essential component of mathematical modelling for answering scientific questions and revealing new insights. Current parameter estimation methods can be inefficient and require too much user intervention. This project will develop novel Bayesian alg ....Advances in Sequential Monte Carlo Methods for Complex Bayesian Models. This project aims to develop efficient statistical algorithms for parameter estimation of complex stochastic models that currently cannot be handled. Parameter estimation is an essential component of mathematical modelling for answering scientific questions and revealing new insights. Current parameter estimation methods can be inefficient and require too much user intervention. This project will develop novel Bayesian algorithms that are optimally automated and efficient by exploiting ever-improving parallel computing devices. The new methods will allow practitioners to process realistic models, enabling new scientific discoveries in a wide range of disciplines such as biology, ecology, agriculture, hydrology and finance.Read moreRead less
Threshold Decisions in Determining Whether to Prosecute Child Sexual Abuse. The objective of this project is new knowledge about the way police and prosecutors make decisions about the prosecution of child sexual assault that could be used to influence policy and practice. Few cases of child sexual abuse reported to the police ever go to court but recent research in New South Wales for the Royal Commission indicates that the proportion has declined sharply over the last decade or so. This projec ....Threshold Decisions in Determining Whether to Prosecute Child Sexual Abuse. The objective of this project is new knowledge about the way police and prosecutors make decisions about the prosecution of child sexual assault that could be used to influence policy and practice. Few cases of child sexual abuse reported to the police ever go to court but recent research in New South Wales for the Royal Commission indicates that the proportion has declined sharply over the last decade or so. This project aims to examine how police and prosecutors decide which cases proceed and why, and how they confer with each other as well as when and how they consult with complainants and their families. This project plans to also develop and test practice tools and principles for police and prosecutors with expected benefits for both them and the families involved.Read moreRead less
Statistical methods for quantifying variation in spatiotemporal areal data. This project aims to develop new statistical methods for extracting insights into spatial and temporal variation in areal data. These tools will extend the Australian Cancer Atlas which provides small area estimates for 20 cancers across Australia. The project is significant because it will allow government and other organisations to reap dividends from investment in collecting spatial information and it will enable mode ....Statistical methods for quantifying variation in spatiotemporal areal data. This project aims to develop new statistical methods for extracting insights into spatial and temporal variation in areal data. These tools will extend the Australian Cancer Atlas which provides small area estimates for 20 cancers across Australia. The project is significant because it will allow government and other organisations to reap dividends from investment in collecting spatial information and it will enable modelled small-area estimates to be released without compromising confidentiality. The expected outcomes include new statistical knowledge and new insights into cancer. The results will benefit the many disciplines, managers and policy makers that make decisions based on geographic data mapped over space and time. Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE240101190
Funder
Australian Research Council
Funding Amount
$451,000.00
Summary
Innovating and Validating Scalable Monte Carlo Methods. This project aims to develop innovative scalable Monte Carlo methods for statistical analysis in the presence of big data or complex mathematical models. Existing approaches to scalable Monte Carlo are only approximate, and their inaccuracies are difficult to quantify. This can have a detrimental impact on data-based decision making. The expected outcomes of this project are scalable Monte Carlo methods that are more accurate, fast and capa ....Innovating and Validating Scalable Monte Carlo Methods. This project aims to develop innovative scalable Monte Carlo methods for statistical analysis in the presence of big data or complex mathematical models. Existing approaches to scalable Monte Carlo are only approximate, and their inaccuracies are difficult to quantify. This can have a detrimental impact on data-based decision making. The expected outcomes of this project are scalable Monte Carlo methods that are more accurate, fast and capable of quantifying inaccuracies. Scientists and decision-makers will benefit from the ability to obtain timely, reliable insights for challenging applications.Read moreRead less
Investigating memory reliability in intoxicated witnesses of crime. Eyewitness testimony is a crucial piece of evidence for solving a crime. Inaccurate testimony leads to miscarriages of justice such as failed prosecutions or false convictions. Many witnesses and victims are affected by alcohol or other drugs during the crime. This project brings together a multidisciplinary team aiming to improve understanding of how intoxication with different substances affects the reliability of victim and w ....Investigating memory reliability in intoxicated witnesses of crime. Eyewitness testimony is a crucial piece of evidence for solving a crime. Inaccurate testimony leads to miscarriages of justice such as failed prosecutions or false convictions. Many witnesses and victims are affected by alcohol or other drugs during the crime. This project brings together a multidisciplinary team aiming to improve understanding of how intoxication with different substances affects the reliability of victim and witness memory accuracy. Crucially, crimes are frequently distressing; therefore the interaction between intoxication and stress urgently requires exploration. This project will significantly advance our understanding of key mechanisms behind drug effects on memory, and support fairer judicial outcomes for all. Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE240100109
Funder
Australian Research Council
Funding Amount
$460,157.00
Summary
Sexual offence interviewing: Towards victim-survivor well-being and justice. This project aims to improve the way victim-survivors are interviewed in sexual offence cases by examining their experiences and perceptions of investigative interview techniques. It expects to generate new knowledge about interview techniques that can promote victim well-being and the disclosure of sensitive information during investigative interviews. Expected outcomes include new theoretical frameworks in the field o ....Sexual offence interviewing: Towards victim-survivor well-being and justice. This project aims to improve the way victim-survivors are interviewed in sexual offence cases by examining their experiences and perceptions of investigative interview techniques. It expects to generate new knowledge about interview techniques that can promote victim well-being and the disclosure of sensitive information during investigative interviews. Expected outcomes include new theoretical frameworks in the field of investigative interviewing and an innovative toolkit of victim-centred training resources to directly inform investigative interview policies and practices in sexual offence cases. Anticipated benefits include better victim experiences of investigative interviews and enhanced justice responses to sexual violence.Read moreRead less