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Statistical data-mining in astrophysics

Cel

The full exploitation of science data is being impeded by statistical and computational intractability. Scientists are now deluged by large, complex data sets, and the scientific value of these data is presently lessened by the laborious efforts needed to analyze them. Therefore, the goal of this project is to develop and deploy new statistical data-mining algorithms to achieve computer-assisted discovery. Such intelligent systems will unburden scientists, allowing them to focus on understanding their resul ts and formulating new hypotheses. This ambition will be achieved through computational efficiency, scalability and autonomy.These research topics will be addressed in the domain of astrophysics, as astronomers are already overwhelmed by data. This multi-d isciplinary (computer science/ statistics/ astrophysics) research will focus on 3 broad areas: â¿¢ Clustering in high dimensional data, e.g. the development of fast n-point correlation function algorithms to fully understand the spatial distribution of ga laxies; â¿¢ Anomaly detection, e.g. the automated discovery of new astronomical phenomena in massive, multi-wavelength data sets; â¿¢ Fast kernel density estimation, e.g. the morphology-density relation of galaxies. These algorithms will be exported to d istributed Grid systems, especially the UK AstroGrid and the US Virtual Observatory. Dr Nichol is a recognized leader in the development of data-mining algorithms for massive astronomical data sets. He returns to the Institute of Cosmology & Gravitatio n, Portsmouth, after 12 years in the USA. The Institute has internationally recognised expertise in theoretical cosmology and grid computing, and is a partner in the UK National Cosmology Supercomputer Consortium, with its own advanced computing resources. Nichol will bring a new aspect of high-tech training to students in Portsmouth through his innovative research and teaching ideas. Once established, he will broaden this training throughout Europe

Zaproszenie do składania wniosków

FP6-2002-MOBILITY-10
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UNIVERSITY OF PORTSMOUTH
Wkład UE
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Adres
Winston Churchill Avenue
PORTSMOUTH
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