课题基金 / 基金详情

Collaborative Research: CyberTraining: Implementation: Small: Train the Trainers as Next Generation Leaders in Data Science for Cybersecurity for Underrepresented Communities

Collaborative Research: CyberTraining: Implementation: Small: Train the Trainers as Next Generation Leaders in Data Science for Cybersecurity for Underrepresented Communities
协作研究:网络培训:实施:小型:将培训师培训为代表性不足社区网络安全数据科学的下一代领导者
批准号:
2321110
负责人:
Yunpeng Zhang
金额:
$32.52万
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:
未结题
起止时间:
2023-09-15 至 2026-08-31

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中文摘要
翻译
在数据科学和网络安全集成方面具有专业知识的劳动力对于维持美国在全球舞台上的竞争力和安全至关重要。培训师,包括教师和专业人士,谁是装备精良的数据科学和网络安全技能是高需求的,以便在代表性不足的社区发挥领导作用,并产生数据驱动的,强大的解决方案,以各种挑战。该项目旨在通过项目团队在休斯顿大学(UH)、Prairie View a&m大学(PVAMU)和阿拉巴马a&m大学(AAMU)这三所少数民族大学的合作努力,解决这一迫切需求。该项目的总体目标是为代表性不足的社区培养下一代网络安全数据科学领导者,为他们提供知识和技能,将这些技术传授给他们的学生和同龄人。该项目探索网络安全领域数据科学的教学、材料、工具和培训环境方面的创新方法。具体而言,该项目的贡献是a)提高参与机构在数据科学和网络安全领域的研究能力,促进hbcu招募和留住高素质的研究人员;b)用新的网络安全数据科学教学模块更新本科和研究生课程,以反映最新进展和最佳实践;c)通过培训师提高非裔美国人和其他少数族裔学生对网络安全数据科学的挑战和机遇的认识;d)开发新的课程材料和源代码,促进项目成果的广泛传播。该项目还通过其系列研讨会将教育效益扩大到来自广泛学科的学习者,从而在医疗保健、绿色能源、智慧城市和制造业等各个行业中更广泛地采用数据科学。该项目致力于推进网络安全数据科学领域的学科教育研究。该奖项反映了美国国家科学基金会的法定使命,并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,被认为值得支持。
英文摘要
A workforce with expertise in the integration of Data Science and Cybersecurity is crucial to maintaining the United States' competitiveness and security in the global arena. Trainers, including faculty and professionals, who are well equipped with both Data Science and Cybersecurity skills are in high demand in order to play leadership roles in underrepresented communities and generate data-driven, robust solutions to various challenges. The project is designed to address this immediate need with the collaborative efforts from the project team across three minority-serving universities with a strong regional presence: University of Houston (UH), Prairie View A&M University (PVAMU), and Alabama A&M University (AAMU). The overarching goal of this project is to train the trainers as next generation leaders in Data Science for Cybersecurity for underrepresented communities, providing them with the knowledge and skills to impart these techniques to their students and peers. This project explores innovative approaches in teaching, materials, tools, and training environments in the Data Science for Cybersecurity field. Specifically, the contributions of this project are a) enhance the research capabilities of the participating institutions in the areas of Data Science and Cybersecurity, promoting recruitment and retention of highly qualified researchers at HBCUs; b) update undergraduate and graduate curricula with new Data Science for Cybersecurity teaching modules to reflect the latest advances and best practices; c) raise awareness among African American and other minoritizy students through trainers of the challenges and opportunities in Data Science for Cybersecurity; and d) develop new course materials and source code and facilitate the widespread dissemination of the project results. The project also expands the educational benefits through its workshop series to learners from a wide range of disciplines, leading to the potential greater adoption of Data Science in various industries such as healthcare, green energy, smart cities, and manufacturing. The project is dedicated to advancing the field of discipline-based education research in the areas of Data Science for Cybersecurity.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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Research on Quantum Field Theory without a Lagrangian Description
  • 批准号:
    24ZR1403900
  • 项目类别:
    省市级项目
  • 资助金额:
    --
  • 批准年份:
    2024
  • 负责人:
    SATOSHI NAWATA
  • 依托单位:
Cell Research
Cell Research
Cell Research (细胞研究)