Understanding and overcoming confusion in consumer financial decisions. This project aims to develop consumer-centred approaches to reducing the harmful effects of confusion in financial decisions by studying superannuation investment and home loan decisions where confused choices are individually and collectively costly. The project intends to develop comprehensive models to capture the full complexity of financial products and the diverse preferences and capability of consumers, then to use ad ....Understanding and overcoming confusion in consumer financial decisions. This project aims to develop consumer-centred approaches to reducing the harmful effects of confusion in financial decisions by studying superannuation investment and home loan decisions where confused choices are individually and collectively costly. The project intends to develop comprehensive models to capture the full complexity of financial products and the diverse preferences and capability of consumers, then to use advanced statistical methods to estimate the benefits of clearer decision-making. The outcomes of this project includes new models of complex financial decisions, and a better understanding of where confusion arises and the effects it may have. Decreased confusion will raise financial well-being and help communities become more resilient to financial shocks.Read moreRead less
Prognosis based network-type feature extraction for complex biological data. This project aims to develop statistical tools that integrate high-throughput molecular data with biological knowledge to make discoveries in complex diseases. This project uses machine learning methods, statistical models and proteomic platforms to identify relationships among clinico-pathologic and molecular measurements. It will produce tools and insights that are intended to accelerate the process of biologically an ....Prognosis based network-type feature extraction for complex biological data. This project aims to develop statistical tools that integrate high-throughput molecular data with biological knowledge to make discoveries in complex diseases. This project uses machine learning methods, statistical models and proteomic platforms to identify relationships among clinico-pathologic and molecular measurements. It will produce tools and insights that are intended to accelerate the process of biologically and clinically significant discoveries in biomedical research. This project will help Australian researchers in statistics and users of statistics (from fields as diverse as biology, ecology, medicine, finance, agriculture and the social sciences) to make better predictions that are easier to understand.Read moreRead less
Discovery of novel microRNA biogenesis and functional components. Discovery of novel microRNA components will provide new strategies for confronting a diverse array of challenges Australia faces, such as the increasing rates of certain cancers in our population, to stresses on our crop plants faced with environmental changes. The biological mechanisms underlying these disparate problems are unified by microRNA involvement in many instances. By finding microRNA controlling factors common to all h ....Discovery of novel microRNA biogenesis and functional components. Discovery of novel microRNA components will provide new strategies for confronting a diverse array of challenges Australia faces, such as the increasing rates of certain cancers in our population, to stresses on our crop plants faced with environmental changes. The biological mechanisms underlying these disparate problems are unified by microRNA involvement in many instances. By finding microRNA controlling factors common to all higher organisms, we expect our community will benefit from the increased knowledge base that will help our researchers adopt new strategies in fighting diseases and improving our agricultural industry.Read moreRead less