DOE Data Reduction for Science: Harvard Pre-Application Deadline

Department of Energy: Data Reduction for ScienceHarvard Pre-Application Deadline: April 27, 2021 at 4:00pmSponsor Pre-Application Deadline: May 6, 2021 at 5:00pmSEAS/FAS/OSP Deadline: May 27, 2021Sponsor Full Proposal Deadline: June 4, 2021Award Amount: $100,000-$400,000 per year for up to three years

The DOE SC program in Advanced Scientific Computing Research (ASCR) has just announced its interest in research applications to explore potentially high-impact approaches in the development and use of data reduction techniques and algorithms to facilitate more efficient analysis and use of massive data sets produced by observations, experiments and simulation.

The principal focus of this program announcement is to support applied mathematics and computer science approaches that address one or more of the identified priority research directions:

1. Effective algorithms and tools that can be trusted by scientists for accuracy and efficiency,
2. Progressive reduction algorithms that enable data to be prioritized for efficient streaming,
3. Algorithms which can preserve information in features and quantities of interest with quantified uncertainty, and
4. Mapping techniques to new architectures and use cases.

Significant innovations will be required in the development of effective paradigms and approaches for realizing the full potential of data reduction for science. Proposed research should not focus only on particular data sets from specific applications, but rather on creating the body of knowledge and understanding that will inform future scientific advances. Consequently, the funding from this announcement is not intended to incrementally extend current research in the area of the proposed project. Rather, the proposed projects must reflect viable strategies toward the potential solution of challenging problems in data reduction for science. It is expected that the proposed projects will significantly benefit from the exploration of innovative ideas or from the development of unconventional approaches. Proposed approaches may include innovative research with one or more key characteristics, such as compression, reduced order models, experiment-specific triggers, filtering, and feature extraction, and may focus on cross-cutting concepts such as scientific machine learning or trust. Preference may be given to pre-applications that include reduction estimates for at least two science applications.

This is a limited submission and only two proposals may be put forward from Harvard as the lead institution. Those interested in submitting an application should send a brief pre-proposal for consideration by the Office of the Vice Provost for Research to vpr@harvard.edu by April 27, 2021 by 4:00pm. Pre-proposals should include the following:

• Name of PI and Senior/Key Personnel and their Institutional Affiliations
• CV of PI and Senior/Key Personnel of no more than two pages in length.
  • Please do not use the NIH Biosketch, or any other template format from an external funding source.
  • In determining which information to present in your CV, please consider this specific funding opportunity, and which of your experiences and honors are most applicable and will present the most qualified and compelling profile in the context of this funding source.
• A clear and concise description of the objectives and technical approach of the proposed research. The pre-application may not exceed two pages, when printed using standard letter-size (8.5 x 11 inch) paper with 1-inch margins (top, bottom, left, and right). The font must not be smaller than 11 point. Figures and references, if included, must fit within the two-page limit.