Funding Opportunity Announcement:
Data Reduction for Science Funding Opportunity
Funding Opportunity Announcement (FOA) Number: DE-FOA-0003266
Total Estimated Funding: $15 Million
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Deadline for Letters of Intent (required):
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March 19, 2024 at 11:59pm ET
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Deadline for Applications:
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May 7, 2024 at 11:59pm ET
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The U.S. Department of Energy’s Office of Science, under the Advanced
Scientific Computing Research Program, is announcing $15 million in available funding to support the advancement of data reduction for science. This research will explore potentially high-impact approaches to develop and use data reduction techniques and
algorithms to facilitate more efficient analysis and use of massive data sets produced by observations, experiments, and simulation. These different types of sources are producing data at rates beyond current capacity to store, analyze, stream, and archive
it in raw form. As a result, many research groups have begun reducing the size of their data sets via techniques such as compression, reduced order models, experiment-specific triggers, filtering, and feature extraction.
This research program seeks to continue to increase the level of mathematical rigor in scientific data reduction to ensure that scientifically relevant constraints on quantities of interest are satisfied, methods can be integrated into scientific workflows,
and methods are implemented in a manner that inspires trust that the desired information is preserved. Data is ubiquitous for every scientific discipline, and it is foundational to the recent, current, and future advancements in scientific machine learning
and artificial intelligence. Machine learning is particularly ripe for data reduction advances, as data reduction can improve the efficiency of learning, and machine learning techniques can be used to reduce data.
Learn more about this funding opportunity announcement and eligibility by visiting the
website.
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