Linkage Infrastructure, Equipment And Facilities - Grant ID: LE0668549
Funder
Australian Research Council
Funding Amount
$280,000.00
Summary
Major upgrade of the computing hardware and software for the widely used BioManager bioinformatic service. ANGIS has been an Australian national facility for bioinformatics since 1991, now with over 4000 users across 150 university schools or departments, government departments, hospitals and research institutes. The grant will provide the computer upgrade and software support needed to handle the enormous increases in database size and complexity and expand the service into new areas of bioinfo ....Major upgrade of the computing hardware and software for the widely used BioManager bioinformatic service. ANGIS has been an Australian national facility for bioinformatics since 1991, now with over 4000 users across 150 university schools or departments, government departments, hospitals and research institutes. The grant will provide the computer upgrade and software support needed to handle the enormous increases in database size and complexity and expand the service into new areas of bioinformatics. Bioinformatics is critical to much of modern biology, and the improvements will enhance research and data analysis in many areas of research, leveraging more value from the research being undertaken by users. Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE150100240
Funder
Australian Research Council
Funding Amount
$315,000.00
Summary
Geometry and Conditioning in Structured Conic Problems. Conic programming allows one to model and solve large industrial problems via modern optimisation methods, such as interior-point algorithms. These methods are efficient and reliable in solving a vast number of problems, however, they fail on a relatively small but significant set of ill-posed instances, thus affecting the overall reliability of the technique. The reason for such behaviour is profound and constitutes one of the major unsolv ....Geometry and Conditioning in Structured Conic Problems. Conic programming allows one to model and solve large industrial problems via modern optimisation methods, such as interior-point algorithms. These methods are efficient and reliable in solving a vast number of problems, however, they fail on a relatively small but significant set of ill-posed instances, thus affecting the overall reliability of the technique. The reason for such behaviour is profound and constitutes one of the major unsolved problems in real complexity: there is no known algorithm that solves conic problems with real data in polynomial time. The project aims to develop a deep understanding of the geometry of conic problems, aiming for the resolution of this fundamental problem in computational theory.Read moreRead less