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

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:
2050943
负责人:
Jianwu Wang
金额:
$29.37万
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2021
资助国家:
美国
项目状态:
已结题
起止时间:
2021-04-01 至 2024-03-31

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中文摘要
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英文摘要
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 to work with experts nationwide. In recent years, the 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 obtain knowledge and insight from them. The program will help students identify frontier research challenges encountered when facing big data in science and engineering, and guide students to conduct research to tackle those challenges using advanced cyberinfrastructure software technologies (big data, distributed machine/deep learning, HPC, etc.) and hardware resources (including big data clusters, CPU clusters and GPU clusters). The program will develop the national workforce in areas of critical need on “Data + Computing + X”. The project thus serves the national interest, as stated by NSF's mission, to promote the progress of science and advance the national prosperity and welfare. By having three phases of training, namely formal instruction, team-based research and dissemination, this REU Site program will i) ignite students' interest in how data science and high-performance computing techniques can aid in 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 domain area of each project; and iii) provide integrated training on crucial professional skills (including skills in collaboration, communication, presentation and writing, and experience in 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 experience 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 experience, 4) complementary professional development activities (such as graduate school preparation, invited talks from established researchers, and interaction with university administers including college deans and department chairs), 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.
期刊论文(8)
专著(0)
科研奖励(0)
会议论文
DOI: 10.13016/m2gbqc-q97l
发表时间: 2021-07
期刊: ArXiv
影响因子: --
作者: [Sahara Ali;Yiyi Huang;Xin Huang;Jianwu Wang]
通讯作者: Sahara Ali;Yiyi Huang;Xin Huang;Jianwu Wang
DOI: 10.1109/bdcat56447.2022.00023
发表时间: 2022-12
期刊: 2022 IEEE/ACM International Conference on Big Data Computing, Applications and Technologies (BDCAT)
影响因子: --
作者: [Jorge L. Gonzalez;Theodore Chapman;Kathryn Chen;Hannah M. Nguyen;Logan Chambers;S. A. Mostafa;]
通讯作者: Jorge L. Gonzalez;Theodore Chapman;Kathryn Chen;Hannah M. Nguyen;Logan Chambers;S. A. Mostafa;
Promising Hyperparameter Configurations for Deep Fully Connected Neural Networks to Improve Image Reconstruction in Proton Radiotherapy
有前景的深度全连接神经网络超参数配置可改善质子放射治疗中的图像重建
DOI: --
发表时间: 2021
期刊: and Security (REU 2021 Symposium
影响因子: --
作者: [York, Sokhna, Ali, Alina, Lashbrooke, David, Yepez-Lopez, Rodrigo, Barajas, Carlos, Gobbert, Matthias, Polf, Jerimy]
通讯作者: Polf, Jerimy
DOI: 10.3389/fphy.2023.903929
发表时间: 2023-02-16
期刊: FRONTIERS IN PHYSICS
影响因子: 3.1
作者: [Barajas, Carlos A. A., Polf, Jerimy C. C., Gobbert, Matthias K. K.]
通讯作者: Gobbert, Matthias K. K.
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