Tracing nature's template: using statistical machine learning to evolve biocatalysts. In this project new computational methods will be developed to design nature-inspired, biological catalysts for industrial purposes. Such methods will enable catalysts to be designed that can improve the effectiveness and environmental footprint of drug development, agricultural and specialist chemical production and environmental remediation.
Discovery Early Career Researcher Award - Grant ID: DE190101486
Funder
Australian Research Council
Funding Amount
$400,000.00
Summary
Animal groups as mobile sensor networks. This project aims to provide biologically inspired solutions to the problems faced by mobile sensor networks. Mobile sensor networks provide a powerful new tool in environmental monitoring and surveillance, however, designing them to be energy efficient while not sacrificing information detection remains a challenge. By immersing animal groups into dynamically changing virtual environments this project will design new efficient mobile sensor networks. The ....Animal groups as mobile sensor networks. This project aims to provide biologically inspired solutions to the problems faced by mobile sensor networks. Mobile sensor networks provide a powerful new tool in environmental monitoring and surveillance, however, designing them to be energy efficient while not sacrificing information detection remains a challenge. By immersing animal groups into dynamically changing virtual environments this project will design new efficient mobile sensor networks. The project is expected to provide solutions to mobile sensor network limitations, benefitting areas including robotics, environmental monitoring and defence.Read moreRead less
Modelling network innovation performance capability: a multidisciplinary approach. Innovation is created in complex network interactions.
By combining agent-based and fuzzy logic modelling, this project will identify combinations of resources to generate new ideas/technologies. This will enable managers and policy makers to understand the mechanisms behind innovation and implement policies aimed at enhancing innovation processes.
Discovery Early Career Researcher Award - Grant ID: DE120100960
Funder
Australian Research Council
Funding Amount
$375,000.00
Summary
Simulation and characterisation of the packing of uniform non-spherical particles. The effect of particle shape on the packing of uniform particles is a fundamental problem in the study of granular materials and is also related to other important scientific problems. This project aims to solve this problem by an innovative computer simulation method, using virtual but insightful numerical results to build solid theories.
Modelling and simulation of self-organised behaviour in biological and bio-inspired systems. Understanding self-organised systems is fundamental in biology and bio-inspired engineering. The project develops sophisticated mathematical modelling techniques and high performance simulation methods for such systems. This will increase our capacity to explain complex biological behaviour and to produce reliable bio-inspired engineering solutions