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
Relative free energies from nonequilibrium simulations: algorithms for determination of binding affinities, conformational states and phase transitions. Leading edge research will enable state of the art techniques in statistical mechanics to be applied to practical problems. All processes in biological, chemical and physical systems are governed by their free energy landscape, often only accessible computationally. This project will lead to an advanced tool for free energy calculation. Advanc ....Relative free energies from nonequilibrium simulations: algorithms for determination of binding affinities, conformational states and phase transitions. Leading edge research will enable state of the art techniques in statistical mechanics to be applied to practical problems. All processes in biological, chemical and physical systems are governed by their free energy landscape, often only accessible computationally. This project will lead to an advanced tool for free energy calculation. Advancement of emerging technologies in nanoscience, porous materials, membrane transport and drug design will benefit from this capability. The project therefore addresses the Priority Goal 'Breakthrough science'. A PhD student and an Early Career Research will be trained in research, gaining a range of valuable skills in theory and simulation. Read moreRead less
International Networks in Applied Bayesian Statistics: improving Australia''s knowledge through intelligent data analysis and modelling. National benefits of this project are fourfold: (i) new international networks between Australia, Southern Africa, France and USA in the priority area of mathematical sciences; (ii) state-of-the-art Bayesian statistical methods for integrating and analyzing non-standard data and diverse information sources, including expert opinion, in order to solve complex pr ....International Networks in Applied Bayesian Statistics: improving Australia''s knowledge through intelligent data analysis and modelling. National benefits of this project are fourfold: (i) new international networks between Australia, Southern Africa, France and USA in the priority area of mathematical sciences; (ii) state-of-the-art Bayesian statistical methods for integrating and analyzing non-standard data and diverse information sources, including expert opinion, in order to solve complex problems in environment, industry, health, defence; (iii) direct contribution to solution of global environmental problems, specifically water quality, threatened species and environmental risk; (iv) superior training of the next generation of the global community of researchers in applied statistics.Read moreRead less
Dissipation and relaxation in statistical mechanics. This project studies the mathematical conditions for relaxation either to equilibrium or to steady states, which is important in predicting behaviour in diverse fields including climate modelling, materials science, nanotechnology and biology. Early career researchers will be involved in the project, gaining valuable skills in theory and simulation.
Improving likelihood estimators: theory and applications to analysing productivity and efficiency and forecasting of probability of economic recession. This project aims to improve one of the most popular statistical methods to empower applied researchers with a more reliable analytical tool. This project will develop mathematical theory and use it to analyse patterns of economic growth, productivity and efficiency of countries. This can be used to forecast probability of entering economic reces ....Improving likelihood estimators: theory and applications to analysing productivity and efficiency and forecasting of probability of economic recession. This project aims to improve one of the most popular statistical methods to empower applied researchers with a more reliable analytical tool. This project will develop mathematical theory and use it to analyse patterns of economic growth, productivity and efficiency of countries. This can be used to forecast probability of entering economic recession, with a focus on Australia.Read moreRead less
Genome-wide Association Studies Of Biomedical Traits And Endophenotypes For Complex Disease
Funder
National Health and Medical Research Council
Funding Amount
$295,804.00
Summary
The burden of common complex diseases, such as cardiovascular disease is substantial to the health care system. These diseases are caused by genes and environments as well as their interactions. The proposed project will identify genes affecting the susceptibility of individuals to complex diseases. Discovery of such genes will be important for their diagnosis, prevention and treatment and may serve as an important resource for future personalized medicine.
Developing And Applying Statistical Genetics Methods To Identify Genes, Molecular Biomarkers And Environmental Agents That Causally Affect Risk Of Complex Musculoskeletal Diseases
Funder
National Health and Medical Research Council
Funding Amount
$707,370.00
Summary
My aim is to identify genes, biological molecules and environmental factors that causally affect risk of osteoporosis and ankylosing spondylitis (a form of autoimmune arthritis) using novel and existing statistical genetics methodologies. My research will advance understanding of the causes of these diseases, identify new opportunities for their treatment, and provide the scientific community with new statistical methods and software to identify factors that causally influence risk of disease.
Properties of nonequilibrium steady states. A nonequilibrium steady state (NESS) occurs when work is performed on a system and the heat so generated is absorbed by a thermostatting mechanism. The system settles into steady state and its properties no longer change. Almost all experimental systems of interest are in a nonequilibrium state, so understanding NESSs is highly significant. Unlike time stationary equilibrium states, the distribution of microstates in a NESS cannot be described by simpl ....Properties of nonequilibrium steady states. A nonequilibrium steady state (NESS) occurs when work is performed on a system and the heat so generated is absorbed by a thermostatting mechanism. The system settles into steady state and its properties no longer change. Almost all experimental systems of interest are in a nonequilibrium state, so understanding NESSs is highly significant. Unlike time stationary equilibrium states, the distribution of microstates in a NESS cannot be described by simple closed form distributions. This project will determine properties, symmetries and extrema of NESS using concepts and theorems developed for studying transient nonequilibrium states, and will also determine if approximate, physically relevant forms of the phase space distributions can be developed.Read moreRead less
Australian Laureate Fellowships - Grant ID: FL190100080
Funder
Australian Research Council
Funding Amount
$3,432,323.00
Summary
New frontiers for nonequilibrium systems. The universe is comprised of systems in states of change or responding to a driving force. Yet a fundamental understanding of these nonequilibrium systems that enables predictive design has eluded scientists to date. This program aims to develop ground-breaking principles and methodologies to predict properties of nonequilibrium systems using both statistical physics and molecular simulations. Significantly, by pioneering new theories and building Austra ....New frontiers for nonequilibrium systems. The universe is comprised of systems in states of change or responding to a driving force. Yet a fundamental understanding of these nonequilibrium systems that enables predictive design has eluded scientists to date. This program aims to develop ground-breaking principles and methodologies to predict properties of nonequilibrium systems using both statistical physics and molecular simulations. Significantly, by pioneering new theories and building Australian capacity in this area, we will be able to understand, control and utilise their distinctive behaviour in design. Expected outcomes and benefits are multi-dimensional, including breakthrough theory and new capability for high-end technologies such as nanofluidics, robotics and batteries.Read moreRead less
The improvement of climate change investigations by developing and applying innovative evolutionary subset time series modelling using semi-parametric sparse-patterned approaches. With an estimated US$6.98 trillion loss indicated in the Stern review, severe climate change will make world climate conditions harsher and more likely include large natural climate disasters. The health of the Australian economy is critically dependent on decisions of environmental managers. However, most problems of ....The improvement of climate change investigations by developing and applying innovative evolutionary subset time series modelling using semi-parametric sparse-patterned approaches. With an estimated US$6.98 trillion loss indicated in the Stern review, severe climate change will make world climate conditions harsher and more likely include large natural climate disasters. The health of the Australian economy is critically dependent on decisions of environmental managers. However, most problems of complexity arising in climate change involve issues on which we do not possess a deep understanding. This project draws upon a set of inter-disciplinary concepts and models centred in neural networks that enable us to advance our understanding of complexity, leading to superior quantitative tools and models to allow for improved environmental decision-making.
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