Multivariate Algorithmics: Meeting the Challenge of Real World computational complexity. This Project will result in better methods for designing the algorithms that all computer applications depend on. Algorithms are the instruction sets that tell computers how to process information. Some information processing tasks are intrinsically difficult, even for computers working at enormous speeds. This Project will deliver new mathematical approaches to overcome these difficulties. More efficient al ....Multivariate Algorithmics: Meeting the Challenge of Real World computational complexity. This Project will result in better methods for designing the algorithms that all computer applications depend on. Algorithms are the instruction sets that tell computers how to process information. Some information processing tasks are intrinsically difficult, even for computers working at enormous speeds. This Project will deliver new mathematical approaches to overcome these difficulties. More efficient algorithmic approaches for difficult problems enable advances in all areas of computer applications such as medical diagnosis and health prediction, national security, communications efficiency, industrial productivity and all fields of science and engineering.Read moreRead less
Local reoptimization for turbocharging heuristics. Theoretical computer science has up until now had little impact on the design of effective heuristics. While data sets may be large, significant structure is almost always present and important to take into account when designing algorithms. Parameterised complexity considers the underlying structure by parameterising not only on the size of the input but also on structural parameters. This project aims to take advantage of the many opportunitie ....Local reoptimization for turbocharging heuristics. Theoretical computer science has up until now had little impact on the design of effective heuristics. While data sets may be large, significant structure is almost always present and important to take into account when designing algorithms. Parameterised complexity considers the underlying structure by parameterising not only on the size of the input but also on structural parameters. This project aims to take advantage of the many opportunities for new theories in the design of new heuristics and in turbocharging existing heuristics for computationally hard problems.Read moreRead less
Linking terrestrial–aquatic fluxes to rectify the Australian carbon balance. This project aims to rectify the Australian carbon balance by determining the amount of terrestrial carbon that is lost to streams and rivers across the country. Through a novel integration of high-resolution hydrochemical and gas measurements, remote sensing and machine learning algorithms, the project intends to generate new knowledge about the links between terrestrial carbon sequestration and aquatic carbon export. ....Linking terrestrial–aquatic fluxes to rectify the Australian carbon balance. This project aims to rectify the Australian carbon balance by determining the amount of terrestrial carbon that is lost to streams and rivers across the country. Through a novel integration of high-resolution hydrochemical and gas measurements, remote sensing and machine learning algorithms, the project intends to generate new knowledge about the links between terrestrial carbon sequestration and aquatic carbon export. Expected outcomes include a refined estimate of the net carbon sequestration potential across Australian biomes and seasons. This should provide significant benefits such as avoiding misalignment of greenhouse gas abatement policies and advancing carbon cycling models and predictions.Read moreRead less