Coarse Grained Parallel Algorithms. Various fields of research face barriers created by problems that are computationally hard and/or require processing of large amounts of data. For example, some computational biochemistry methods on protein or gene sequences can not be scaled up to data sets required for human health research because of performance problems. Parallel computing enables new research by increasing the size of solvable problems. In addition to fundamental parallel computing resear ....Coarse Grained Parallel Algorithms. Various fields of research face barriers created by problems that are computationally hard and/or require processing of large amounts of data. For example, some computational biochemistry methods on protein or gene sequences can not be scaled up to data sets required for human health research because of performance problems. Parallel computing enables new research by increasing the size of solvable problems. In addition to fundamental parallel computing research, this project studies parallel algorithms for structure-based drug design and protein-protein interaction prediction that will enable new biochemistry research, as well as parallel algorithms for data cubes that will help enable the next generation of very large data warehouses.Read moreRead less
Efficient Pre-Processing of Hard Problems: New Approaches, Basic Theory and Applications. Computers store even larger amounts of data about all aspects of human and industrial activity. However, they have not become significantly better at solving common problems in optimization and search. Traditional complexity theory indicates many of these problems require algorithms that are very unlikely to exist. The Parameterized Complexity approach allows us to obtain very efficient algorithms for a lar ....Efficient Pre-Processing of Hard Problems: New Approaches, Basic Theory and Applications. Computers store even larger amounts of data about all aspects of human and industrial activity. However, they have not become significantly better at solving common problems in optimization and search. Traditional complexity theory indicates many of these problems require algorithms that are very unlikely to exist. The Parameterized Complexity approach allows us to obtain very efficient algorithms for a large variety of problems, but the machinery required was diverse and complicated. This research will organize the machinery into a new approach that systematically finds good algorithms by applying simplifications around a parameter of the domain of the problem. As a result, efficient algorithms are obtained for many diverse areas.Read moreRead less
Generic complexity in computational topology: breaking through the bottlenecks. The project will focus on key computational problems in three-dimensional topology, with the aims of illuminating the theoretical limitations of such problems, developing new computational tools for solving them, and applying these tools to a variety of applications. The project will generate theoretical research, practical software, and rich experimental data.
Approximate proximity for applications in data mining and visualization. Data Mining, pattern recognition and visualization of relational information are all important data analysis techniques in which it is essential to determine which data points are in the vicinity of others. The huge size of the data sets involved and the need for real-time interaction preclude the use of conventional methods for the precise computation of the proximity information required. This project will develop efficie ....Approximate proximity for applications in data mining and visualization. Data Mining, pattern recognition and visualization of relational information are all important data analysis techniques in which it is essential to determine which data points are in the vicinity of others. The huge size of the data sets involved and the need for real-time interaction preclude the use of conventional methods for the precise computation of the proximity information required. This project will develop efficient algorithms and data structures for gathering high-quality approximations of the full proximity information, and will use these innovations as the basis for new, practical tools for visualization, and clustering in data mining.Read moreRead less
Modelling interactions of spray droplets with plants. This project addresses the National Research Priority of an environmentally sustainable Australia by developing sophisticated mathematical models and interactive software that will identify environmentally friendlier technologies to efficiently deliver agrichemicals while minimising large scale water usage. National benefits will accrue from the provision for postdoctoral, PhD and IT staff training, while direct links with industry will provi ....Modelling interactions of spray droplets with plants. This project addresses the National Research Priority of an environmentally sustainable Australia by developing sophisticated mathematical models and interactive software that will identify environmentally friendlier technologies to efficiently deliver agrichemicals while minimising large scale water usage. National benefits will accrue from the provision for postdoctoral, PhD and IT staff training, while direct links with industry will provide technology transfer to end-users to ensure community uptake. The project will benefit rural and regional communities by providing long-term solutions in the areas of water use and quality, pesticide pollution reduction, and improved environment and human health care.Read moreRead less
Algorithmic engineering and complexity analysis of protocols for consensus. Opinions, rankings, observations, votes, gene sequences, sensor-networks in security systems or climate models. Massive datasets and the ability to share information at unprecedented speeds, makes finding the most central representative, the Consensus Problem, extremely complex. This research delivers new insights and new, efficient algorithms.