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NSF Student Travel Grant for the 2022 ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2022)

NSF Student Travel Grant for the 2022 ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2022)
NSF 学生旅费资助 2022 年 ACM SIGKDD 知识发现和数据挖掘会议 (KDD 2022)
批准号:
2223561
负责人:
Yue Ning
金额:
$2.5万
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2022
资助国家:
美国
项目状态:
已结题
起止时间:
2022-06-15 至 2024-05-31

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中文摘要
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英文摘要
This grant provides support for 25 U.S.-based graduate students to participate in the 28th ACM SIGKDD conference on Knowledge Discovery and Data Mining (KDD 2022), which will be held in Washington D.C. from August 14 -18, 2022. KDD is an annual conference that presents the world's premier research in data mining. In the past, the total number of KDD participants has been in excess of 3000. The conference covers topics in the data mining lifecycle, including algorithms, software and systems, and applications. The conference will also focus on related areas such as artificial intelligence, machine learning, data management, and information retrieval. The selection committee will select recipients of the support based on merit and need and place particular emphasis on diversity in the selection process.As an interdisciplinary conference, KDD brings together researchers and practitioners from academia, industry, and governments who work on all aspects of data mining and data science problems. The conference is highly competitive and focuses on training and mentoring students. It includes a technical program with regular peer-reviewed papers in the form of oral and poster presentations, as well as panel discussions and invited talks by leading experts in academia and industry. Besides the technical program, the conference features activities such as workshops, tutorials, panels, posters, project showcases. These will provide a comprehensive multi-facet learning experience to students at all levels. The award will be advertised and the results will be announced at the KDD 2022 website (https://www.kdd.org/kdd2022/) as well as various data mining mailing lists.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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CAREER: Towards Deep Interpretable Predictions for Multi-Scope Temporal Events
  • 批准号:
    2047843
  • 项目类别:
    Continuing Grant
  • 资助金额:
    $57.19万
  • 财政年份:
    2021
  • 负责人:
    Yue Ning
  • 依托单位:
CRII: III: Learning Dynamic Graph-based Precursors for Event Modeling
  • 批准号:
    1948432
  • 项目类别:
    Standard Grant
  • 资助金额:
    $17.5万
  • 财政年份:
    2020
  • 负责人:
    Yue Ning
  • 依托单位:
海外基金