REU Site: Online Interdisciplinary Big Data Analytics in Science and Engineering

REU 网站：科学与工程领域的在线跨学科大数据分析

• 批准号: 2348755
• 负责人: Matthias Gobbert
• 金额: $ 36.28万
• 依托单位: University of Maryland Baltimore County
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2024
• 资助国家: 美国
• 起止时间: 2024-02-01 至 2027-01-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2348755&HistoricalAwards=false
• 关键词: REU; Site; Online; Interdisciplinary; Big

This REU Site program will provide 8-week summer online research experiences to undergraduates on how to utilize modern data science and high-performance computing (HPC) techniques to process and analyze big data in many science and engineering disciplines such as Atmospheric Science, Mechanical Engineering, and Medicine. The REU Site program will be conducted purely online to allow students to conduct research without traveling and work with experts nationwide. In recent years, astronomical growth of available datasets in many science and engineering disciplines often requires big data analytics techniques to efficiently and effectively process the large datasets and gain knowledge from them. The program will help students identify frontier research challenges when facing big data in science and engineering, and guide students to conduct research to tackle the research challenges using advanced cyberinfrastructure software technologies (e.g., big data, distributed machine/deep learning, HPC) and hardware resources such as big data clusters, CPU clusters, and GPU clusters. The program will provide development of the national workforce in areas of critical need on "Data + Computing + X", where "X" is a variety of application areas. By having three phases of training -- formal instruction, team-based research, and dissemination -- this REU Site program will i) encourage students' interests in how data science and high-performance computing techniques could help the scientific discovery process via interdisciplinary research projects; ii) provide interdisciplinary team-based research experiences via guidance from research mentors, graduate assistants, and interdisciplinary collaborators in the application area of each project; and iii) provide integrated training on crucial professional skills (e.g., collaboration, communication, presentation, and writing) and experiences with scientific paper preparation and presentation. This REU Site will provide a unique and comprehensive program integrating the following elements under the guidance of the faculty team who have extensive experiences in interdisciplinary research and online education: 1) frontier research connecting advanced cyberinfrastructure techniques with big data challenges in science and engineering, 2) online research experience that leverages modern communication tools, 3) team-based interdisciplinary research and communication experiences, 4) complementary professional development activities (e.g., graduate school preparation, invited talks from established researchers, and interaction with university leadership), 5) educational research on online undergraduate training experiences.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.

该REU网站计划将为本科生提供为期8周的暑期在线研究体验，介绍如何利用现代数据科学和高性能计算（HPC）技术来处理和分析许多科学和工程学科（如大气科学，机械工程和医学）中的大数据。REU网站计划将纯粹在网上进行，让学生进行研究，而无需旅行，并与全国各地的专家工作。近年来，许多科学和工程学科中可用数据集的天文数字式增长通常需要大数据分析技术来有效地处理大型数据集并从中获取知识。该计划将帮助学生识别科学和工程中面临大数据时的前沿研究挑战，并指导学生使用先进的网络基础设施软件技术（例如，大数据、分布式机器/深度学习、HPC）和硬件资源，如大数据集群、CPU集群和GPU集群。该计划将在“数据+计算+ X”的关键需求领域提供国家劳动力的发展，其中“X”是各种应用领域。 通过三个阶段的培训-正式教学，基于团队的研究和传播-这个REU网站计划将i）鼓励学生对数据科学和高性能计算技术如何通过跨学科研究项目帮助科学发现过程的兴趣; ii）通过研究导师，研究生助理，以及每个项目应用领域的跨学科合作者;以及iii）提供关键专业技能的综合培训（例如，协作、沟通、演示和写作）以及科学论文准备和演示的经验。该REU网站将提供一个独特而全面的计划，在具有跨学科研究和在线教育丰富经验的教师团队的指导下，整合了以下元素：1）前沿研究将先进的网络基础设施技术与科学和工程领域的大数据挑战联系起来，2）利用现代通信工具的在线研究经验，3）团队为基础的跨学科研究和交流经验，4）补充专业发展活动（例如，研究生院的准备，邀请知名研究人员的演讲，以及与大学领导的互动），5）在线本科生培训经验的教育研究。该奖项反映了NSF的法定使命，并通过使用基金会的智力价值和更广泛的影响审查标准进行评估，被认为值得支持。