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SGER: Planning for a Cross-Cutting Initiative in Computational Discovery

SGER: Planning for a Cross-Cutting Initiative in Computational Discovery
SGER:规划计算发现的跨领域计划
批准号:
0652536
负责人:
Leonard Schulman
金额:
$10.0万
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2007
资助国家:
美国
项目状态:
已结题
起止时间:
2007-01-15 至 2007-12-31

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中文摘要
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英文摘要
The initiative must be designed to attract the best researchers from both the Theoretical Computer Science (TCS) community and, crucially, the other scientific and engineering disciplines in which the ideas are to be applied. In preparing a detailed initiative, it is essential to incorporate the advice and cooperation of leading researchers in all these fields. For this purpose it is proposed to hold two two-day planning workshops, with thirty to forty participants in each. About a third of the participants will be invited speakers, a third will beinvited discussants, and a third will be selected from the TCS community. The distinguishing feature of these workshops will be their multidisciplinary nature; experts from different areas will be invited and asked to focus on the computational lens and its use in solving problems from their field. The first workshop is tentatively planned for early December, 2006 at Princeton University, and the second for mid-March, 2007 at Caltech. Because of the wideranging nature of the scientific disciplines involved, the first workshop will focus on Biological and Earth Sciences, and the second on Physical and Mathematical Sciences. A report for the NSF based on the workshops will be completed by Summer, 2007.The intellectual merit of this proposal is the development of viable, promising courses of future interaction between CS and other disciplines. The broader impact will be that upon follow-on research: both directly by participants in the workshops, but ultimately much more widely if the workshops lead to an NSFcross-cutting initiative.
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NSF-BSF: AF: Small: Algorithmic and Information-Theoretic Challenges in Causal Inference
  • 批准号:
    2321079
  • 项目类别:
    Standard Grant
  • 资助金额:
    $61.6万
  • 财政年份:
    2023
  • 负责人:
    Leonard Schulman
  • 依托单位:
NSF-BSF: AF: Small: Identifying Functional Structure in Data
  • 批准号:
    1909972
  • 项目类别:
    Standard Grant
  • 资助金额:
    $40.0万
  • 财政年份:
    2019
  • 负责人:
    Leonard Schulman
  • 依托单位:
AF: Small: Algorithms and Information Theory for Causal Inference
  • 批准号:
    1618795
  • 项目类别:
    Standard Grant
  • 资助金额:
    $45.0万
  • 财政年份:
    2016
  • 负责人:
    Leonard Schulman
  • 依托单位:
AF: Small: Algorithms for Inference
  • 批准号:
    1319745
  • 项目类别:
    Standard Grant
  • 资助金额:
    $47.39万
  • 财政年份:
    2013
  • 负责人:
    Leonard Schulman
  • 依托单位:
海外基金