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Conference: Statistical Foundations of Data Science and their Applications

Conference: Statistical Foundations of Data Science and their Applications
会议:数据科学的统计基础及其应用
批准号:
2304646
负责人:
Matias Cattaneo
金额:
$2.5万
依托单位:
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2023
资助国家:
美国
项目状态:
已结题
起止时间:
2023-02-01 至 2024-01-31

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中文摘要
翻译
该奖项支持为期三天的题为“数据科学的统计基础及其应用”的多元化和包容性会议,将于2023年5月8日至10日在普林斯顿大学举行。数据科学是一门蓬勃发展的广泛学科,它结合了各种现有领域,包括古典和现代统计学,生物统计学,计量经济学和机器学习,到目前为止,它已经改变了社会,行为和生物医学科学以及金融,工业和政府进行定量研究的方式。会议的主要目标是将基础和应用数据科学各个方面的初级和高级学者聚集在一起,同时也为指导初级和代表性不足的学者提供独特的机会(例如,代表性不足的少数民族、妇女和残疾人)在广泛的学科中。虽然数据科学结合并增强了许多科学研究领域的最佳效果,但令人遗憾的是,这些特定领域的学者并不总是以协同的方式相互作用。此外,对于年轻学者来说,往往很难接触到其分支领域之外的领域,阻碍了他们的智力和专业发展。这些智力障碍有时会减少多样性和包容性,因为不同学术和专业社区存在社会效率低下的智力孤岛。会议的一个关键目标是高度跨学科,对新的知识思想和方法持开放态度,希望能够接触到学术界,工业界和政府。会议的另一个同样重要且高度互补的关键目标是通过为他们提供专门定制的活动来培养初级和代表性不足的学者,此外还为他们提供与来自世界各地的许多顶级数据科学学者互动和交流的机会。有关会议详情的网站是https://orfe.princeton.edu/events/dsconf/This奖,反映了NSF的法定使命,并被认为值得通过使用基金会的知识价值和更广泛的影响审查标准进行评估来支持。
英文摘要
This award supports a diverse and inclusive three-day conference titled "Statistical Foundations of Data Science and their Applications" to take place at Princeton University on May 8-10, 2023. Data science is a thriving broad discipline that combines various existing fields including classical and modern statistics, biostatistics, econometrics and machine learning, and has by now transformed the way that quantitative research is conducted in the social, behavioral and biomedical sciences, as well as in finance, industry and government more generally. The main goal of the conference is to bring together junior and senior scholars working on all aspects of foundational and applied data science, while also offering unique opportunities for mentoring junior and underrepresented scholars (e.g., underrepresented minorities, women, and persons with disabilities) across a broad range of disciplines. While data science combines and potentiates the best of many scientific areas of study, it is regrettably not always the case that scholars working of those specific areas interact with each other in a synergistic way. Furthermore, for young scholars it is often hard to reach out outside their subfields, hampering their intellectual and professional development. These intellectual barriers sometimes reduce diversity and inclusion due to the socially inefficient intellectual silos present in different academic and professional communities. A key goal of the conference is to be highly interdisciplinary and open to new intellectual ideas and approaches, hoping to reach out to academia, industry and government. Another equally important and highly complementary key goal of the conference is to foster junior and underrepresented scholars by offering them specifically tailored activities to such goal, in addition to offering them opportunities to interact and network with many top data science scholars from around the world that will be in attendance. The website with details about the conference is https://orfe.princeton.edu/events/dsconf/This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
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会议论文
Partitioning-Based Learning Methods for Treatment Effect Estimation and Inference
  • 批准号:
    2241575
  • 项目类别:
    Standard Grant
  • 资助金额:
    $45.32万
  • 财政年份:
    2023
  • 负责人:
    Matias Cattaneo
  • 依托单位:
Nonparametric Estimation and Inference with Network Data
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    2210561
  • 项目类别:
    Standard Grant
  • 资助金额:
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  • 财政年份:
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  • 负责人:
    Matias Cattaneo
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New Developments in Methodology for Program Evaluation
  • 批准号:
    2019432
  • 项目类别:
    Standard Grant
  • 资助金额:
    $46.0万
  • 财政年份:
    2020
  • 负责人:
    Matias Cattaneo
  • 依托单位:
Collaborative Research: Robust Inference for Kernel Smoothing and Related Problems
  • 批准号:
    1947805
  • 项目类别:
    Standard Grant
  • 资助金额:
    $28.49万
  • 财政年份:
    2020
  • 负责人:
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  • 依托单位:
海外基金