REU Site: Big Data Analytics
REU Site: Big Data Analytics
批准号:
1852343
负责人:
Roman Garnett
金额:
$36.0万
依托单位:
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2019
资助国家:
美国
项目状态:
已结题
起止时间:
2019-04-01 至 2024-03-31
中文摘要
这个本科生研究体验(REU)网站是一个为期10周的暑期项目,旨在全国范围内招募有前途和渴望的学生,帮助他们发现计算机科学研究的刺激和兴奋。该网站特别针对那些家庭院校在科学、技术、工程和数学(STEM)领域的研究机会有限的学生,因此可能无法获得必要的接触机会来点燃对研究职业的渴望,以及女性,她们广泛观察到的离开技术管道可能会被一个有意义和具有挑战性的研究暑期所抵消。我们的REU网站专注于数据分析的技术和方法及其应用。我们对数据科学的关注使学生能够参与跨各个领域的跨学科研究,为具有不同兴趣范围的学生创造广泛的吸引力。数据科学还为工业界、非营利组织和政府机构提供了许多参与的机会。REU允许学生获得专业知识,使他们成为研究项目的重要贡献者,并在完成本科学位后成为STEM领域许多不同类型职位的抢手候选人。这个REU网站的目标是让学生(1)发展数据分析的研究技能;(2)为实质性研究项目做出贡献,涉及开发数据分析的新方法或应用;(3)培养对研究的欣赏和热情,以及对计算机研究生学习的理解。除了在个人项目中进行核心研究(通常与其他REU学生和研究生组成团队)之外,学生们还作为一个群体参加各种活动,包括技术和社会导向的新兵训练营,有演讲和海报的夏末研讨会,研究技能研讨会,与教师见面的活动,以及行业演讲者的演讲。由系和学院组织的社会活动,以及促进学生社会活动,进一步帮助建立群体认同。该网站特别寻求从大学招收工程本科研究机会有限的学生,并通过计算机管道解决女性代表性不足的问题。参加REU的学生将:(1)接触到数据分析在计算机科学中的许多应用,(2)通过他们的特定项目、新兵训练营和其他辅助活动获得特定技术技能和一般研究技能的专业知识,以及(3)具备技术竞争优势、知识和动力,在STEM领域从事研究工作。学生对大型数据集分析的前沿研究做出贡献,这些研究通常发表在顶级场所。研究主题包括使用大数据来解决无家可归问题,药物设计,开发新的并行算法来处理大型数据集。这个REU网站培训和吸引下一代STEM研究人员和数据分析专业人士,特别关注女性和研究机会有限的本科院校的学生。重点是吸引女性进入计算机领域,并通过使她们从事具有社会重要性和现实适用性的项目来帮助留住她们,并特别强调为她们提供成功所需的动力和工具。学生主要来自本科院校,包括3-2项目的90所合作院校,以及计算机领域的女性网络(尤其是格蕾丝·霍珀会议)。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
This Research Experiences for Undergraduates (REU) site is a 10-week summer program that seeks to nationally recruit promising and eager students and help them to discover the stimulation and excitement of research in computer science. The site especially targets recruitment from students whose home institutions have limited research opportunities in Science, Technology, Engineering and Math (STEM) and therefore might not be given the necessary exposure to kindle a desire for a career in research, as well as women, whose widely-observed departure from the technical pipeline could be counteracted by a meaningful and challenging summer of research. Our REU site is focused on technologies and methods for data analysis, and applications thereof. Our focus on data science allows students to participate in inherently interdisciplinary research that crosses a variety of fields, creating broad appeal for students with a diverse range of interests. Data science also opens numerous opportunities for engagement with industry, nonprofits, and government agencies. The REU allows students to gain expertise that makes them valuable contributors to research projects and sought-after candidates for many different types of positions in STEM fields once they finish their undergraduate degrees. The objectives of this REU site are that students will (1) develop research skills in data analysis; (2) contribute to a substantive research project involving development of new methods for, or applications of, data analysis; (3) develop an appreciation and passion for research, as well as an understanding of what it is like to pursue graduate study in computing. In addition to the core research immersion in individual projects (often in teams with other REU students and graduate students), students also participate in various activities as a cohort, including a boot camp for technical and social orientation, an end-of-summer symposium with talks and posters, research skills seminars, meet-the-faculty events, and talks by industry speakers. Social events organized by the department and school, and facilitation of student social events further help to build cohort identity. The site specifically seeks to recruit students from colleges with limited opportunities for undergraduate research in engineering, and to address the underrepresentation of women through the computing pipeline. Students participating in the REU will: (1) be exposed to the many applications of data analytics across computer science, (2) gain expertise in specific technical skills and general research skills via their specific project, boot camp, and other ancillary activities, and (3) be equipped with a technical competitive advantage, knowledge, and motivation to pursue a research career in a STEM field. Students contribute to cutting-edge research in the analysis of large datasets, often published in top venues. Research topics range from using big data to combat homelessness, to drug design, to developing new parallel algorithms for processing large datasets. This REU site trains and engages the next generation of STEM researchers and professionals in data analytics, with a special focus on women and on students from undergraduate institutions with limited research opportunities. There is a focus on attracting women to the computing pipeline and helping to retain them by enabling their work on projects with social importance and real-world applicability, and special emphasis on providing them with both the motivation and the tools needed for success. Students are recruited heavily from undergraduate institutions, including 90 partner colleges in a 3-2 program, and through networks of women in computing (especially the Grace Hopper conference).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.
期刊论文(1)
专著(0)
科研奖励(0)
会议论文
Supporting Multi-messenger Astrophysics with Fast Gamma-ray Burst Localization
通过快速伽马射线暴定位支持多信使天体物理学
DOI:
10.1109/urgenthpc54802.2021.00008
发表时间:
2021
期刊:
2021 IEEE/ACM HPC for Urgent Decision Making (UrgentHPC
影响因子:
--
作者:
[Wheelock, Jacob, Kanu, William, Sudvarg, Marion, Xiao, Zhili, Buhler, Jeremy D., Chamberlain, Roger D., Buckley, James H.]
通讯作者:
Buckley, James H.
REU Site: Big Data Analytics
-
批准号:2244152
-
项目类别:Standard Grant
-
资助金额:$39.93万
-
财政年份:2023
-
负责人:Roman Garnett
-
依托单位:
Collaborative Research: Accelerating the Discovery of Electronic Materials through Human-Computer Active Search
-
批准号:1940224
-
项目类别:Standard Grant
-
资助金额:$30.59万
-
财政年份:2019
-
负责人:Roman Garnett
-
依托单位:
CAREER: Active Machine Learning for Automating Scientific Discovery
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批准号:1845434
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项目类别:Continuing Grant
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资助金额:$49.77万
-
财政年份:2019
-
负责人:Roman Garnett
-
依托单位:
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批准号:52172255
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批准号:41340011
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资助金额:20.0万元
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批准年份:2013
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负责人:钱凤魁
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依托单位: