Computational methods for population-size-dependent branching processes. Branching processes are the primary mathematical tool used to model populations that evolve randomly in time. Most key results in the theory are derived under the simplifying assumption that individuals reproduce and die independently of each other. However, this assumption fails in most real-life situations, in particular when the environment has limited resources or when the habitat has a restricted capacity. This project ....Computational methods for population-size-dependent branching processes. Branching processes are the primary mathematical tool used to model populations that evolve randomly in time. Most key results in the theory are derived under the simplifying assumption that individuals reproduce and die independently of each other. However, this assumption fails in most real-life situations, in particular when the environment has limited resources or when the habitat has a restricted capacity. This project aims to develop novel and effective algorithmic techniques and statistical methods for a class of branching processes with dependences. We will use these results to study significant problems in the conservation of endangered island bird populations in Oceania, and to help inform their conservation management.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE200100200
Funder
Australian Research Council
Funding Amount
$418,398.00
Summary
Next generation causal inference methods for biological data. This project aims to develop next generation causal inference methods for analysing biological data especially the single cell sequencing data and their applications in cell biology. Although Artificial Intelligence and Statistical Machine Learning have been applied successfully in many fields, including biological research, there is still a serious lack of methods for interpreting and reasoning about the mechanism of biological syste ....Next generation causal inference methods for biological data. This project aims to develop next generation causal inference methods for analysing biological data especially the single cell sequencing data and their applications in cell biology. Although Artificial Intelligence and Statistical Machine Learning have been applied successfully in many fields, including biological research, there is still a serious lack of methods for interpreting and reasoning about the mechanism of biological systems, the ultimate goal of research in many areas. Efficient data-driven causality discovery approaches developed by the project will be a timely and significant contribution to the knowledge of biology and statistics as well as the battle against health threats.
Read moreRead less
New Horizons in Quinonedimethide Chemistry. Quinonedimethides (QDMs) are organic molecules with a notorious reputation for instability, hence they are poorly understood and an underexploited resource. This project will unite the ideally suited computational and experimental skills of the CIs to perform the first thorough investigation into fundamental QDM chemistry. It aims to map structure-reactivity in QDMs, investigate their ability to rapidly generate complex structures, and demonstrate thei ....New Horizons in Quinonedimethide Chemistry. Quinonedimethides (QDMs) are organic molecules with a notorious reputation for instability, hence they are poorly understood and an underexploited resource. This project will unite the ideally suited computational and experimental skills of the CIs to perform the first thorough investigation into fundamental QDM chemistry. It aims to map structure-reactivity in QDMs, investigate their ability to rapidly generate complex structures, and demonstrate their potential in spintronics and other applications. Anticipated outcomes include powerful and general new synthetic concepts, methods, strategies and tactics. This should provide significant benefits, such as better ways to manufacture important medicines and other materials.Read moreRead less
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
Mathematical modelling of information flow in social networks. This proposal aims to develop new mathematical and statistical methods to understand information flow in social networks. By using novel information theoretic techniques, it will create new methods to characterise social information flow in social networks. These tools will allow derivation of fundamental limits of predictability for AI methods applied to digital data. New mathematics of information flow will produce insights into so ....Mathematical modelling of information flow in social networks. This proposal aims to develop new mathematical and statistical methods to understand information flow in social networks. By using novel information theoretic techniques, it will create new methods to characterise social information flow in social networks. These tools will allow derivation of fundamental limits of predictability for AI methods applied to digital data. New mathematics of information flow will produce insights into social influence in online social networks. Benefits include: better understanding of how echo chambers may form in social networks, predictive models for how misinformation can spread online such as during an emergency, and a framework for intercomparison of AI methods applied to digital data on individuals. Read moreRead less
Advanced mathematical models and methods for a randomly-varying world. This project aims to develop advanced stochastic models and novel techniques, to analytically obtain performance measures and to efficiently simulate the time evolution. This project also plans to apply new models and methods to address important problems in ecology and epidemiology. The outputs of this project will advance knowledge in mathematics as well as in the intended application areas, including ultimately in improved ....Advanced mathematical models and methods for a randomly-varying world. This project aims to develop advanced stochastic models and novel techniques, to analytically obtain performance measures and to efficiently simulate the time evolution. This project also plans to apply new models and methods to address important problems in ecology and epidemiology. The outputs of this project will advance knowledge in mathematics as well as in the intended application areas, including ultimately in improved understanding, modelling, and tracking of the spread of diseases.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE230101174
Funder
Australian Research Council
Funding Amount
$443,154.00
Summary
Harnessing life-course transitions to optimise time-use behaviour habits. At every stage of life, how we use our time is one of the greatest determinants of our happiness, productivity, social wellbeing and quality of life. Time-use habits, for better or worse, are entrenched in daily routines that are difficult to break. This project aims to use existing population datasets to identify when during their life people are most likely to change their time-use habits, and to describe who may be at g ....Harnessing life-course transitions to optimise time-use behaviour habits. At every stage of life, how we use our time is one of the greatest determinants of our happiness, productivity, social wellbeing and quality of life. Time-use habits, for better or worse, are entrenched in daily routines that are difficult to break. This project aims to use existing population datasets to identify when during their life people are most likely to change their time-use habits, and to describe who may be at greatest risk of making unfavourable changes (e.g., replacing physical activity with sedentary time, not getting enough sleep). Expected outcomes include new analytical methods to understand time-use routines and new knowledge to inform future time-use improvement strategies to enable Australians to live their best life.Read moreRead less
Switchable and stereocontrolled photoredox catalysis. This project aims to develop new catalytic synthetic reactions for the rapid and more direct functionalisation of organic compounds under mild conditions with the use of visible light. An integrated experimental and computational approach will be used to design potent visible-light photocatalysts that retain the advantages of standard photoredox catalysis but with the added ability to intercept and, thus control, reactive intermediates in sit ....Switchable and stereocontrolled photoredox catalysis. This project aims to develop new catalytic synthetic reactions for the rapid and more direct functionalisation of organic compounds under mild conditions with the use of visible light. An integrated experimental and computational approach will be used to design potent visible-light photocatalysts that retain the advantages of standard photoredox catalysis but with the added ability to intercept and, thus control, reactive intermediates in situ. This will enable the control of stereochemistry in photoredox reactions – not possible with standard catalysts - and establish other useful synthetic transformations. These strategies will make it easier to prepare valuable classes of organic molecules – efficiently, safely, and cost-effectively.
Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE230101642
Funder
Australian Research Council
Funding Amount
$357,299.00
Summary
Earth’s mid-life crisis: recipe for a habitable planet? This project aims to establish the state and nature of the physical Earth systems (climate, topography, geography, erosion, carbon cycle, oxygen cycle) during the Neoproterozoic Era that made our planet habitable to complex life. By analysing these systems together, fundamental drivers and contributions to making a habitable planet will be untangled. Expected outcomes include the first ever series of climate models of this time period, as w ....Earth’s mid-life crisis: recipe for a habitable planet? This project aims to establish the state and nature of the physical Earth systems (climate, topography, geography, erosion, carbon cycle, oxygen cycle) during the Neoproterozoic Era that made our planet habitable to complex life. By analysing these systems together, fundamental drivers and contributions to making a habitable planet will be untangled. Expected outcomes include the first ever series of climate models of this time period, as well a series of digital reconstructions of the physical systems themselves. Sedimentary hosted ore deposits, such as copper and cobalt, are formed partly as a function of erosion and climate, allowing us to provide a mechanistic driver to their formation, and consequently exploration.Read moreRead less