REU Site: Non-Invasive Deep Brain-Computer Interfaces
REU Site: Non-Invasive Deep Brain-Computer Interfaces
批准号:
2244450
负责人:
Jing He
金额:
$32.37万
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:
2023-05-01 至 2025-04-30
中文摘要
这个本科生研究体验(REU)网站将使每年八名本科生能够在肯纳索州立大学(KSU)从事健壮的智能非侵入性深部脑-计算机接口(BCI)系统的前沿研究课题。这个跨学科项目的总体目标是为本科生提供一个多导师的学术环境。REU网站将利用BCI技术的创造性潜力来吸引和扩大妇女和未被充分代表的少数群体在计算和工程领域的参与。KSU REU项目的重点是招收具有广泛学科背景、对从事计算机和信息工程研究工作感兴趣的学生。为了实现这一目标,该REU网站将:(I)每个暑期邀请八名学生参加为期10周的BCI和相关技术研究项目,并与其他分领域合作进行指导研究项目;(Ii)提供这些研究领域常见工具和技术的培训;(Iii)激励参与的学生将STEM视为职业道路,并在研究生水平上从事STEM职业;(Iv)专门针对女性和代表性不足的少数群体的参与,以及(V)鼓励在本国学院和大学研究机会有限的本科生参与。每个REU学生的指导团队不仅包括来自计算机科学的成员,还包括来自不同背景的成员,包括数据科学、信息技术和工程技术。学生将参加各种活动,以拓宽未来的职业机会,如研究生学习,研究科学家,杰出的科学和工程师职位,以及教师的职业道路。此外,REU的学生将向目标会议和期刊提交他们的期末研究论文。研究人员和导师都是KSU的女教员,这可以吸引更多代表不足的群体参加这个项目。重新录取的学生将被提供一个创新的多学科STEM网络学习环境和动手实践。通过KSU REU项目,8名REU学生将在经验丰富的教师和行业导师的指导下,全面从事全周期研究项目,掌握专业研究技能。这些研究项目将高度关注与脑机接口(BCI)相关的主题,涵盖健壮智能的高级主题,使用非侵入性脑电(EEG)数据。这个REU网站将(I)让本科生参与物联网设备、医疗保健、大数据分析、网络安全和深度机器学习方法的集成设计,(Ii)鼓励学生参加学生数据挖掘比赛,(Iii)帮助REU学生增强他们的陈述技能、研究能力以及专利和出版物准备,(Iv)为即将就其本科后职业方向做出决定的学生提供变革性的职业体验,以及(V)为女性和代表性不足的本科生提供强大的跨学科研究机会。KSU REU项目将组织实地考察、研讨会、研讨会、海报日活动和各种社会活动,以丰富教育和研究经验。参与的本科生开展的研究将推动BCI技术在各种应用中的应用,如医疗保健(言语和运动障碍、心理健康、公共卫生和疾病传播)、同理心培训、隐私保护数据分析和机器学习。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
This Research Experiences for Undergraduates (REU) Site will enable eight undergraduate students each year to undertake cutting-edge research topics in Robust Intelligent non-invasive Deep brain-computer interface (BCI) Systems at Kennesaw State University (KSU). The overall goal of this interdisciplinary program is to provide undergraduate students with a multi-mentor academic environment. The REU Site will use the creative potential of BCI technology to attract and broaden the participation of women and underrepresented minorities in the Computing and Engineering fields. The KSU REU program focuses on recruiting students from a broad range of disciplinary backgrounds who are interested in pursuing research careers in Computer and Information Engineering. To achieve this, this REU site will: (i) involve eight students per summer for a 10-week long research project in BCI and related technology with mentored research projects conducted in collaboration with other subfields, (ii) provide training in tools and technologies that are common in these research areas, (iii) inspire participating students to consider STEM as a career path and pursue STEM career at the graduate level, (iv) specifically target participation of women and underrepresented minorities, and (v) encourage participation of undergraduate students who have limited research opportunities at their home colleges and universities. The mentoring team for each REU student includes members not only from computer science but also from diverse backgrounds, including data science, information technology, and engineering technology. Students will participate in various activities to broaden future career opportunities such as graduate study, research scientists, outstanding science and engineer positions, and faculty career path. In addition, REU students will submit their final research papers to target conferences and journals. The investigators and mentors are all women faculty at KSU, which can attract more underrepresented groups to this program.Recruited students will be offered an innovative multi-disciplinary STEM cyber-learning environment and hands-on practices. Through the KSU REU program, eight REU students will fully work on whole-cycle research projects and master professional research skills under the guidance of experienced faculty and industry mentors. These research projects will have a high-level focus on Brain-Computer Interface (BCI)-related topics covering advanced topics in robust intelligence, using non-invasive electroencephalography (EEG) data. This REU site will (i) engage undergraduates in the integrated design of IoT devices, healthcare, big data analysis, cyber security, and deep machine learning methods, (ii) encourage students to participate in student data mining competitions, (iii) help the REU students enhance their presentation skills, research abilities, as well as patent and publication preparation, (iv) provide a transformative career experience for students who are on the brink of making decisions about their post-undergraduate career directions, and (v) provide strong interdisciplinary research opportunities for women and underrepresented undergraduate Students. KSU REU program will organize field trips, workshops, seminars, poster day events, and various social activities to enrich the educational and research experiences. The research carried out by the participating undergraduate students will advance the state of the art in incorporating BCI techniques for various applications such as healthcare (speech and motor disability, mental health, public health and disease spreading), empathy training, privacy preserving data analytics, and machine learning.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(3)
专著(0)
科研奖励(0)
会议论文
Brain-Computer Interface and VR/AR for the Diagnosis and Intervention of ADHD and ASD: A Preliminary Review
脑机接口和 VR/AR 用于 ADHD 和 ASD 诊断和干预的初步综述
DOI:
--
发表时间:
2023
期刊:
2023 Proceedings of the ISCAP Conference
影响因子:
--
作者:
[Maximum Streeter, Zhigang Li]
通讯作者:
Maximum Streeter, Zhigang Li
RAIN-COMPUTER INTERFACE (BCI) IN NEUROSCIENCE FROM 2008 TO 2023: A SURVEY
2008 年至 2023 年神经科学中的 RAIN-计算机接口 (BCI):一项调查
DOI:
--
发表时间:
2024
期刊:
2024 Proceeding of Southern Association of Information Systems
影响因子:
--
作者:
[Anqi zheng,]
通讯作者:
Anqi zheng,
Machine Learning Load Balancing Algorithms in SDN-enabled Massive IoT Networks
支持 SDN 的大规模物联网网络中的机器学习负载均衡算法
DOI:
10.1109/ipccc59175.2023.10253834
发表时间:
2023
期刊:
IEEE
影响因子:
--
作者:
[Harbin, Aaron, Baldwin, Kane, Mhatre, Jui, Lee, Ahyoung, Lee, Hoseon]
通讯作者:
Lee, Hoseon
ABI Innovation: Advanced informatics and effective algorithms to enable CryoEM protein structure prediction and density analysis
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批准号:1356621
-
项目类别:Continuing Grant
-
资助金额:$58.97万
-
财政年份:2014
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负责人:Jing He
-
依托单位:
国内基金
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批准号:52172255
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资助金额:58万元
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负责人:瞿三寅
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基于重要农地保护LESA(Land Evaluation and Site Assessment)体系思想的高标准基本农田建设研究
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批准号:41340011
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负责人:钱凤魁
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