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REU Site: Experience the Full Data Science Pipeline through Research and Practice

REU Site: Experience the Full Data Science Pipeline through Research and Practice
REU 网站:通过研究和实践体验完整的数据科学流程
批准号:
2244480
负责人:
Jia Chen
金额:
$38.99万
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:
2023-04-01 至 2026-03-31

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中文摘要
翻译
数据科学是一个新兴的交叉学科领域,它使用科学方法从各种类型的数据中提取洞察力和知识,这些数据的来源包括科学实验、数字过程、传感器、社交媒体、移动设备等。公司、政府和当地机构正求助于数据科学家来挖掘此类数据以获得洞察力,目的是改善业务运营、造福公共和社会服务、推进科学发现或了解用户行为。虽然数据科学是尖端应用和研究的核心,但目前的劳动力不仅在数量上,而且在多样性方面,都缺乏满足需求的能力。这种多样性差距虽然是大学和该行业目前面临的一个重大挑战,但也提供了一个巨大的机遇:扩大和多样化数据科学研究和实践的覆盖范围,因为它正在加州大学河滨分校等顶级研究机构教授和进阶,面向全国范围内才华横溢、目前服务不足的学生群体。基于本科生研究对所有学生在科学和工程领域的成功有重要贡献这一理念,这个REU网站的建立旨在通过为期八周的暑期计划,通过研究和实践为10名本科生提供完整的数据科学管道体验,并提供全年可选的后续研究、专业发展和职业指导活动。该REU网站将向全国招收的本科生展示完整的数据科学管道:从数据获取、数据建模到真实世界的应用。主要活动包括为期八周的暑期计划(新兵训练营、研究项目、住房和旅行、道德培训、海报演示、社交和指导活动)和为期一年的参与。该项目的目标是向更广泛的受众提供有意义的数据科学研究机会,包括女性、代表性不足的少数族裔,以及来自加州大学河滨分校等没有重大研究活动的机构的经济困难本科生。学生将主要从少数族裔服务和研究II大学、没有计算机科学或计算机博士课程的机构和社区学院招收。参与的学生将参与研究项目,包括大数据管理、统计数据建模、基因组数据挖掘和社交媒体挖掘。最后,学生参与者的研究项目,尽管它们是为适应暑期实习的范围而量身定做的,但都解决了数据科学研究中的前沿问题,并具有推动各自数据科学子领域发展的潜力。该奖项反映了NSF的法定使命,并通过使用基金会的智力优势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
Data Science is an emerging interdisciplinary field that uses scientific methods to extract insights and knowledge from various types of data whose origin includes scientific experiments, digital processes, sensors, social media, mobile devices, and more. Companies, government, and local agencies are turning to data scientists to mine such data for insights with the goal of improving business operations, benefitting public and social services, advancing scientific discovery, or understanding user behavior. While data science is at the heart of cutting-edge applications and research, the current workforce is ill-equipped to meet the demand, not only in numbers but also in diversity. Such a diversity gap, albeit being a major current challenge that universities and the industry face, also presents a tremendous opportunity: broadening and diversifying the reach of data science research and practice, as it is being taught and advanced at top-tier research institutions such as the University of California Riverside, to a highly talented and currently under-served portion of the student population nationwide. Motivated by the notion that undergraduate research contributes significantly to success in science and engineering for all students, this REU Site is established to offer 10 undergraduate students the full data science pipeline experience through research and practice via the eight-week summer program with optional follow-up research, professional development, and career mentoring activities throughout the year.This REU Site will expose undergraduate students recruited nationally to the full data science pipeline: from data acquisition, data modeling, to real-world applications. The main activities contain the eight-week summer program (boot-camp, research projects, housing and travel, ethics training, poster presentation, social interaction, and mentoring activities) and year-long engagement. The goal of this project is to provide meaningful data science research opportunities to a broader audience, including women, underrepresented minorities, and economically disadvantaged undergraduate students from institutions that do not have major research operations like the University of California Riverside. Students will be recruited primarily from minority serving and Research II universities, institutions without Computer Science or Computing Ph.D. programs, and community colleges. Participating students will engage with research projects including big data management, statistical data modeling, genomics data mining, and social media mining. Finally, the student participants’ research projects, even though they are tailored to fit within the confines of a summer internship, all address cutting-edge problems in data science research and have the potential for advancing the respective data science sub-areas.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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