Scholarships, Academic, and Social Supports to Provide Low-Income Transfers Students Opportunities for Nurtured Growth in AI
奖学金、学术和社会支持为低收入转学生提供促进人工智能发展的机会
基本信息
- 批准号:2321986
- 负责人:
- 金额:$ 249.05万
- 依托单位:
- 依托单位国家:美国
- 项目类别:Continuing Grant
- 财政年份:2024
- 资助国家:美国
- 起止时间:2024-04-15 至 2029-03-31
- 项目状态:未结题
- 来源:
- 关键词:
项目摘要
This project will contribute to the national need for well-educated scientists, mathematicians, engineers, and technicians by supporting the retention and graduation of high-achieving, low-income students with demonstrated financial need at the University of Central Florida (UCF). As one of the largest universities in the nation, UCF is among the top three institutions enrolling transfer students and is recognized as a Hispanic Serving Institution. Over its five-year duration, this project will fund scholarships to fifty unique full-time students who are pursuing Bachelor of Science (BS) or Master of Science (MS) degrees in the artificial intelligence (AI) fields of Computer Science, Computer Vision, Computer Engineering, Data Analytics, and Statistics & Data Science. With BS+MS programs in place, many of these students will be able to complete an MS degree in just 12 months after completion of a BS degree. All scholarship recipients will enter the program as transfer students entering the university and will receive support until graduation. These students are at a critical phase in their academic careers, at a time when obstacles of many varieties have the greatest potential to cause students to reconsider their paths, becoming vulnerable to attrition. Each program participant is given a faculty mentor, who has expertise in his/her field of study, and a peer mentor, who is near graduation for a degree in that field. The mentors serve as a personal guides for the student as he/she navigates unknown territory at a new institution and begins challenging coursework. Scholarships provide freedom to focus on studies, without the additional burden of finding ways to pay for it. Altogether, the support of a scholarship, a mentor, and a community of like-minded students, promises to reduce the obstacles students face, keep them interested in their field of study, and motivate them to excel academically. Students will be streamlined into existing research groups or industrial internships or REUs, which will later be used to place qualified students into the workforce.The overall goal of this project is to increase STEM degree completion of low-income, high-achieving students with demonstrated financial need. The specific aims of the project are to (i) ensure scholars are retained past the first year, (ii) ensure scholars persist and complete a BS degree in high-need fields of AI, and (iii) substantially increase the number of MS degrees in AI fields. To achieve the project goals, we will (a) provide transfer students a strong sense of belonging and establish their identities as AI scholars, (b) develop scholars’ proficiency in AI through mentoring and advanced coursework, with potential for research and internships, and (c) provide clear pathways to MS degree completion with financial support. The expected outcomes are 90% retention rate past the first year, 90% participation rate in internships or research projects, and 60% acceptance rate into MS degree programs in AI fields. To ensure the project remains on track for achieving its goals, an external evaluator will monitor the selection and recruitment process, along with graduation and retention rates, as well as student and mentor activities. Program results will be disseminated through the program webpage, reports at conferences and article publication. This project is funded by NSF’s Scholarships in Science, Technology, Engineering, and Mathematics program, which seeks to increase the number of low-income academically talented students with demonstrated financial need who earn degrees in STEM fields. It also aims to improve the education of future STEM workers, and to generate knowledge about academic success, retention, transfer, graduation, and academic/career pathways of low-income students.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.
该项目将有助于对受过良好教育的科学家,数学家,工程师和技术人员的国家需要,通过支持高成就,低收入学生的保留和毕业,证明在中央佛罗里达大学(UCF)的经济需要。 作为全国最大的大学之一,UCF是招收转学生的前三名机构之一,并被公认为西班牙裔服务机构。 在五年的时间里,该项目将为50名在计算机科学,计算机视觉,计算机工程,数据分析和统计数据科学等人工智能(AI)领域攻读理学学士(BS)或理学硕士(MS)学位的全日制学生提供奖学金。随着BS+MS课程的实施,这些学生中的许多人将能够在完成BS学位后的短短12个月内完成MS学位。所有奖学金获得者将作为转学生进入大学,并将获得支持,直到毕业。这些学生正处于其学术生涯的关键阶段,此时各种各样的障碍最有可能导致学生重新考虑他们的道路,变得容易流失。 每个项目参与者都有一个教师导师,谁在他/她的研究领域的专业知识,和一个同伴导师,谁是在该领域的学位毕业附近。导师作为学生的个人指南,因为他/她在一个新的机构导航未知的领域,并开始具有挑战性的课程。奖学金提供了专注于学习的自由,而无需寻找支付方式的额外负担。总而言之,奖学金,导师和志同道合的学生社区的支持,有望减少学生面临的障碍,保持他们对学习领域的兴趣,并激励他们在学业上取得优异成绩。学生将被精简到现有的研究小组或工业实习或雷乌斯,这将是后来用来放置合格的学生进入劳动力。这个项目的总体目标是增加低收入,高成就的学生与证明经济需要的STEM学位完成。 该项目的具体目标是:(i)确保学者在第一年后被保留下来,(ii)确保学者坚持并完成人工智能高需求领域的学士学位,以及(iii)大幅增加人工智能领域的硕士学位数量。 为了实现项目目标,我们将(a)为转学生提供强烈的归属感,并建立他们作为人工智能学者的身份,(B)通过指导和高级课程来提高学者在人工智能方面的熟练程度,并有可能进行研究和实习,以及(c)在财政支持下提供完成MS学位的明确途径。 预期结果是第一年的留存率达到90%,实习或研究项目的参与率达到90%,人工智能领域硕士学位课程的录取率达到60%。 为确保该项目如期实现其目标,一名外部评估员将监测甄选和征聘过程,沿着毕业率和保留率以及学生和导师活动。 方案成果将通过方案网页、会议报告和文章出版物传播。 该项目由NSF的科学,技术,工程和数学奖学金计划资助,该计划旨在增加低收入学术人才的数量,这些学生表现出经济需求,并获得STEM领域的学位。它还旨在改善未来STEM工作者的教育,并提供有关低收入学生的学术成功、保留、转学、毕业和学术/职业途径的知识。该奖项反映了NSF的法定使命,并且通过使用基金会的智力价值和更广泛的影响力审查标准进行评估,被认为值得支持。
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
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Mubarak Shah其他文献
CodaMal: Contrastive Domain Adaptation for Malaria Detection in Low-Cost Microscopes
CodaMal:低成本显微镜中疟疾检测的对比域适应
- DOI:
10.48550/arxiv.2402.10478 - 发表时间:
2024 - 期刊:
- 影响因子:0
- 作者:
I. Dave;Tristan de Blegiers;Chen Chen;Mubarak Shah - 通讯作者:
Mubarak Shah
Lung-CADex: Fully automatic Zero-Shot Detection and Classification of Lung Nodules in Thoracic CT Images
Lung-CADex:胸部 CT 图像中肺结节的全自动零样本检测和分类
- DOI:
- 发表时间:
2024 - 期刊:
- 影响因子:0
- 作者:
Furqan Shaukat;Syed Muhammad Anwar;Abhijeet Parida;Van Lam;M. Linguraru;Mubarak Shah - 通讯作者:
Mubarak Shah
Out-of-Distribution Detection Using Union of 1 -Dimensional Subspaces: Supplementary Materials
使用一维子空间并集进行分布外检测:补充材料
- DOI:
- 发表时间:
2021 - 期刊:
- 影响因子:0
- 作者:
Alireza Zaeemzadeh;N. Bisagno;Zeno Sambugaro;Nicola Conci;Nazanin Rahnavard;Mubarak Shah - 通讯作者:
Mubarak Shah
Robust Image Geolocalization
强大的图像地理定位
- DOI:
- 发表时间:
2023 - 期刊:
- 影响因子:0
- 作者:
Akhil Arularasu;P. Kulkarni;Gaurav Kumar;Mubarak Shah - 通讯作者:
Mubarak Shah
Machine Vision and Applications Understanding Human Behavior from Motion Imagery
机器视觉和应用从运动图像理解人类行为
- DOI:
- 发表时间:
2003 - 期刊:
- 影响因子:0
- 作者:
Mubarak Shah - 通讯作者:
Mubarak Shah
Mubarak Shah的其他文献
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{{ truncateString('Mubarak Shah', 18)}}的其他基金
REU Site: Research Experience for Undergraduates in Computer Vision
REU 网站:计算机视觉本科生的研究经验
- 批准号:
2349386 - 财政年份:2024
- 资助金额:
$ 249.05万 - 项目类别:
Standard Grant
REU Site: Research Experience for Undergraduates in Computer Vision
REU 网站:计算机视觉本科生的研究经验
- 批准号:
2050731 - 财政年份:2021
- 资助金额:
$ 249.05万 - 项目类别:
Standard Grant
CRI: II-New: Cognitive Mechanisms and Computational Modeling of Gaze Control During Scene Free Viewing, Visual Search, and Daily Tasks
CRI:II-新:场景自由观看、视觉搜索和日常任务期间注视控制的认知机制和计算模型
- 批准号:
1823276 - 财政年份:2018
- 资助金额:
$ 249.05万 - 项目类别:
Standard Grant
STEM TRansfer Students Opportunity for Nurtured Growth (STRONG)
STEM 转学生提供培育成长的机会(强)
- 批准号:
1742424 - 财政年份:2018
- 资助金额:
$ 249.05万 - 项目类别:
Standard Grant
REU Site: Research Experience for Undergraduates in Computer Vision
REU 网站:计算机视觉本科生的研究经验
- 批准号:
1757858 - 财政年份:2018
- 资助金额:
$ 249.05万 - 项目类别:
Standard Grant
BIGDATA: IA: Distributed Semi-Supervised Training of Deep Models and Its Applications in Video Understanding
BIGDATA:IA:深度模型的分布式半监督训练及其在视频理解中的应用
- 批准号:
1741431 - 财政年份:2017
- 资助金额:
$ 249.05万 - 项目类别:
Standard Grant
RET Site: Research Experiences for Teachers in Computer Vision and Bio-Medical Imaging
RET 网站:计算机视觉和生物医学成像教师的研究经验
- 批准号:
1542439 - 财政年份:2016
- 资助金额:
$ 249.05万 - 项目类别:
Standard Grant
REU Site: NSF Research Experience for Undergraduates in Computer Vision
REU 网站:NSF 计算机视觉本科生研究经验
- 批准号:
1461121 - 财政年份:2015
- 资助金额:
$ 249.05万 - 项目类别:
Standard Grant
REU Site: Research Experience for Undergraduates in Computer Vision
REU 网站:计算机视觉本科生的研究经验
- 批准号:
1156990 - 财政年份:2012
- 资助金额:
$ 249.05万 - 项目类别:
Standard Grant
Students Actualizing Talent at Education?s Subsequent Stages (STATESS)
学生在教育后续阶段实现才能(STATESS)
- 批准号:
0966249 - 财政年份:2010
- 资助金额:
$ 249.05万 - 项目类别:
Standard Grant
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