REU Site: Applied Artificial Intelligence for Advanced Applications
REU 网站:高级应用的应用人工智能
基本信息
- 批准号:2349370
- 负责人:
- 金额:$ 46.16万
- 依托单位:
- 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:2024-04-15 至 2027-03-31
- 项目状态:未结题
- 来源:
- 关键词:
项目摘要
Artificial Intelligence (AI) is a game-changer in advancing data-driven solutions in areas from personalized healthcare, national security, smart transportation, e-commerce, to online education. Increased computing power, the availability of large digital data sets, and algorithmic advances in machine learning and Generative AI have made it possible for AI research and development to create new sectors of the economy and revitalize industries. Development of talent in AI is of utmost importance to ensure continued advancement and economic growth in AI with the potential for significant economic impact and quality-of-life improvements for all members of our society. Yet there are limited opportunities for undergraduate students to further their education and research in Artificial Intelligence despite its recognition as a STEM field of great importance and visibility in society recently (given the rise of ChatGPT and Generative AI). This program fills this gap by providing undergraduate students underrepresented in STEM the access to engage in meaningful Artificial Intelligence research. In particular, this project provides students from institutions across the country the opportunity to participate in AI research in WPI's Department of Computer Science and the Data Science and Artificial Intelligence programs via Research Undergraduate Experience summer sites successfully operated at WPI since 2016. The focus of this site is to tackle societal challenges in tackling bias and information integrity, advancing personalized digital health, and modeling critical resources such as renewable energy and human mobility - all interlinked concerns of national importance. This project provides a unique educational experience for undergraduate students by engaging them in vibrant research projects through which they tackle critical societal challenges via Artificial Intelligence tools and techniques. The students work in research teams, closely mentored by WPI faculty advisors and graduate students, and have ownership of a project for the duration of the summer. Undergraduate students participating in this project are trained in the best-practices AI-modeling pipeline from data preparation, model development, model evaluation, to model deployment. Further, they design and apply these techniques to solve impactful problems. Given the opportunity to solve pressing problems related to society and our well-being, the students are empowered to make a difference. To supplement the educational and research skill development of students, a weekly seminar series on professional development covering topics from research inquiry, ethics, communication skills to career opportunities in AI are held and networking events with industry partners are offered. Their involvement in this research program provides students the interpersonal communication, professional networking skills, and AI research skills that they would not encounter in the classroom, and thus encourages the students to find their interest and consider graduate studies. This project ultimately prepares students for AI-related professions with the potential for exciting leadership career opportunities -- thus contributing to the STEM workforce and the US economic prosperity.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.
人工智能 (AI) 是推动个性化医疗、国家安全、智能交通、电子商务和在线教育等领域数据驱动解决方案的游戏规则改变者。计算能力的提高、大型数字数据集的可用性以及机器学习和生成人工智能的算法进步,使得人工智能研究和开发能够创造新的经济领域并振兴工业。人工智能人才的发展对于确保人工智能的持续进步和经济增长至关重要,并有可能对我们社会所有成员产生重大经济影响和生活质量改善。 然而,尽管人工智能最近被认为是一个在社会上具有重要意义和知名度的 STEM 领域(考虑到 ChatGPT 和生成式 AI 的兴起),但本科生在人工智能方面继续深造和研究的机会有限。 该计划通过为 STEM 中代表性不足的本科生提供参与有意义的人工智能研究的机会来填补这一空白。特别是,该项目通过自 2016 年以来在 WPI 成功运营的研究型本科生体验暑期项目,为来自全国各地机构的学生提供了参与 WPI 计算机科学系以及数据科学和人工智能项目的人工智能研究的机会。该网站旨在应对社会挑战,消除偏见和信息完整性,推进个性化数字健康,并对可再生能源和人口流动等关键资源进行建模——所有这些都是与国家重要性相关的相互关联的问题。 该项目通过让本科生参与充满活力的研究项目,为他们提供独特的教育体验,通过人工智能工具和技术应对关键的社会挑战。学生们在研究团队中工作,受到 WPI 教师顾问和研究生的密切指导,并在整个夏季拥有一个项目的所有权。 参与该项目的本科生接受了从数据准备、模型开发、模型评估到模型部署的最佳实践人工智能建模流程培训。此外,他们设计并应用这些技术来解决有影响的问题。 由于有机会解决与社会和我们福祉相关的紧迫问题,学生们有能力做出改变。为了补充学生的教育和研究技能发展,每周举办一次关于专业发展的研讨会系列,涵盖人工智能领域的研究探究、道德、沟通技巧和职业机会等主题,并提供与行业合作伙伴的交流活动。他们参与这个研究项目为学生提供了在课堂上不会遇到的人际沟通、专业网络技能和人工智能研究技能,从而鼓励学生找到自己的兴趣并考虑研究生学习。该项目最终使学生为人工智能相关职业做好准备,并有可能获得令人兴奋的领导职业机会,从而为 STEM 劳动力和美国经济繁荣做出贡献。该奖项反映了 NSF 的法定使命,并通过使用基金会的评估进行评估,认为值得支持。智力价值和更广泛的影响审查标准。
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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Elke Rundensteiner其他文献
Multi-domain Emotion Detection using Transfer Learning
使用迁移学习的多域情绪检测
- DOI:
10.2991/phico-16.2017.12 - 发表时间:
2023 - 期刊:
- 影响因子:0
- 作者:
J. Devlin;Ming;Kenton Lee;Xavier Ferrer;T. Nuenen;J. Such;Maryam Hasan;Elke Rundensteiner;Yen;Ssu;Mau;Yi;Yaodong Yu;Yi - 通讯作者:
Yi
AlloyGAN: Domain-Promptable Generative Adversarial Network for Generating Aluminum Alloy Microstructures
AlloyGAN:用于生成铝合金微观结构的领域提示生成对抗网络
- DOI:
10.1109/icmla58977.2023.00249 - 发表时间:
2023-12-15 - 期刊:
- 影响因子:0
- 作者:
Biao Yin;Yangyang Fan;Nicholas Josselyn;Elke Rundensteiner - 通讯作者:
Elke Rundensteiner
Elke Rundensteiner的其他文献
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{{ truncateString('Elke Rundensteiner', 18)}}的其他基金
Collaborative Research: ELEMENTS: Tuning-free Anomaly Detection Service
合作研究:Elements:免调优异常检测服务
- 批准号:
2103832 - 财政年份:2021
- 资助金额:
$ 46.16万 - 项目类别:
Standard Grant
Collaborative Research: ELEMENTS: Tuning-free Anomaly Detection Service
合作研究:Elements:免调优异常检测服务
- 批准号:
2103832 - 财政年份:2021
- 资助金额:
$ 46.16万 - 项目类别:
Standard Grant
NRT-HDR: Data-Driven Sustainable Engineering for a Circular Economy
NRT-HDR:数据驱动的循环经济可持续工程
- 批准号:
2021871 - 财政年份:2020
- 资助金额:
$ 46.16万 - 项目类别:
Standard Grant
III: Small: Fair Decision Making by Consensus: Interactive Bias Mitigation Technology
III:小:共识公平决策:交互式偏差缓解技术
- 批准号:
2007932 - 财政年份:2020
- 资助金额:
$ 46.16万 - 项目类别:
Standard Grant
III:Small: Outlier Discovery Paradigm
III:小:异常值发现范式
- 批准号:
1910880 - 财政年份:2019
- 资助金额:
$ 46.16万 - 项目类别:
Standard Grant
REU SITE: DATA SCIENCE RESEARCH FOR HEALTHY COMMUNITIES IN THE DIGITAL AGE
REU 网站:数字时代健康社区的数据科学研究
- 批准号:
1852498 - 财政年份:2019
- 资助金额:
$ 46.16万 - 项目类别:
Standard Grant
III: Small: Scalable Event Trend Analytics For Data Stream Inquiry
III:小型:用于数据流查询的可扩展事件趋势分析
- 批准号:
1815866 - 财政年份:2018
- 资助金额:
$ 46.16万 - 项目类别:
Standard Grant
REU SITE: Data Science Research for Safe, Sustainable and Healthy Communities
REU 站点:安全、可持续和健康社区的数据科学研究
- 批准号:
1560229 - 财政年份:2016
- 资助金额:
$ 46.16万 - 项目类别:
Standard Grant
Student Travel Support for U.S. Graduate Students to Participate in EDBT/ICDT 2012
为美国研究生参加 EDBT/ICDT 2012 提供学生旅行支持
- 批准号:
1144371 - 财政年份:2012
- 资助金额:
$ 46.16万 - 项目类别:
Standard Grant
CGV: Small: Model-Driven Visual Analytics on Streams
CGV:小型:模型驱动的流可视化分析
- 批准号:
1117139 - 财政年份:2011
- 资助金额:
$ 46.16万 - 项目类别:
Continuing Grant
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2244461 - 财政年份:2023
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