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Details of Grant 

EPSRC Reference: EP/W015080/1
Title: DMS-EPSRC Collaborative Research: Advancing Statistical Foundations and Frontiers from and for Emerging Astronomical Data Challenges
Principal Investigator: van Dyk, Professor D A
Other Investigators:
Researcher Co-Investigators:
Project Partners:
Center for Astrophysics(Harvard & Smith) Harvard University University of California Davis
University of Michigan
Department: Mathematics
Organisation: Imperial College London
Scheme: Standard Research - NR1
Starts: 01 April 2022 Ends: 31 March 2025 Value (£): 272,688
EPSRC Research Topic Classifications:
Statistics & Appl. Probability
EPSRC Industrial Sector Classifications:
No relevance to Underpinning Sectors
Related Grants:
Panel History:  
Summary on Grant Application Form
Statistical theory and methods play a fundamental role in scientific discovery and advancement, including in modern astronomy, where data are collected on increasingly massive scales and with more varieties and complexity. New technology and instrumentation are spawning a diverse array of emerging data types and data analytic challenges, which in turn require and inspire ever more innovative statistical methods and theories. This proposal is guided by the dual aims of advancing statistical foundations and frontiers, motivated by astronomical problems and providing principled data analytic solutions to challenges in astronomy. The CHASC International Center for Astrostatistics has an extensive track record in accomplishing both tasks. This NSF-EPSRC project leverages CHASC's track record to make progress in several new projects. Fitting sophisticated astrophysical models to complex data that were collected with high-tech instruments, for example, often involves a sequence of statistical analyses. Several UK-led projects center on developing new statistical methods that properly account for errors and carry uncertainty forward within such sequences of analyses. Additional US-led work will focus on developing theoretical properties of novel statistical estimation procedures to address data-analytic challenges associated with solar flares and X-ray observations. Other US-led projects involve fast and automatic detection of astronomical objects such as galaxies from 2D or even 4D data. The PIs will develop statistical theory and methods in the context of these projects, building statistical foundations and pushing the frontiers of statistics forward for broad impact that will extend well beyond astrostatistics. The PIs plan to offer effective methods and algorithms for tackling emerging challenges in astronomy, with the aspiration of promoting such principled data-analytic methods among researchers in astronomy. Its provision of free software via the CHASC GitHub Software Library will enable the distribution and impact of the proposed methods and algorithms.

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Organisation Website: http://www.imperial.ac.uk