REU Site: Research Experience for Undergraduates in Big Data Analytics and Machine Learning

REU 网站：大数据分析和机器学习本科生的研究经验

• 批准号: 2050175
• 负责人: Simone Ludwig
• 金额: $ 51.43万
• 依托单位: North Dakota State University Fargo
• 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
• 起止时间: 2021-09-01 至 2024-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2050175&HistoricalAwards=false
• 关键词: REU; Site; Research; Experience; Undergraduates

The continued growth and development of any nation depends on two important factors: the evolution of sustainable technology and the availability of a skilled workforce that can apply the technology for the betterment of society and manage its growth through research and development. Further, to maintain the strategic position of the United States of America in both technology development and science and engineering education, it is critical to encourage and motivate a new generation of American students to pursue advanced studies in STEM disciplines. The best way to achieve this goal is to bring highly motivated undergraduate students together within an active research group and introduce them to intellectual excitement. This will allow these students to get actively involved in research projects, help them think independently, foster creativity, and develop confidence and skills necessary to work on research projects and succeed in their chosen career paths. It will also provide them access to strong mentors and the opportunity to begin developing their network with their classmates and seniors in their research group.This REU Site aims to achieve three distinct goals: 1) provide a deeper understanding of big data analytics and machine learning concepts; 2) increase passion and research skills in data analytics and machine learning, and inculcate professional skills and ethical behavior among students during their undergraduate education, especially those from underrepresented population groups and/or with limited access to this research at their home institutions; and 3) provide international research experience to prepare a global STEM/data-savvy workforce. This project will support thirty undergraduate students (over a three-year period) for a 10-week long high-impact research internship experience. During this research internship period, the participants will gain 4-weeks long international research experience in real world big data and machine learning projects at the University of Chile (UCHILE), a strong research institution in South America. Students from any STEM discipline across the nation will be recruited for this program. Specifically, efforts will be made to recruit at least 50% participants form underrepresented population including women, at least one third from outside North Dakota, and at least 60% from outside NDSU. This project will introduce undergraduate students to unique applications of big data and machine learning tools to manage digital engineering systems. Students will develop deeper understanding of these new concepts and advance new models/algorithms to solve engineering problems for industries such as energy infrastructure, cyber manufacturing, precision agriculture, and several other cyber physical systems. Lastly, students will work on both theory and practice to develop better insight for solving real engineering problems and demonstrating their applications in real life scenarios. The international research experience will further enable these students to join the global workforce by gaining global research and cultural experience.This project is jointly funded by the Division of Engineering Education and Centers (Directorate for Engineering), and the Established Program to Stimulate Competitive Research (EPSCoR).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.

任何国家的持续增长和发展都取决于两个重要因素：可持续技术的发展和熟练劳动力的可用性，这些劳动力可以应用技术来改善社会，并通过研究和开发来管理其增长。此外，为了保持美国在技术发展和科学与工程教育方面的战略地位，鼓励和激励新一代美国学生在STEM学科中继续深造至关重要。实现这一目标的最佳方法是将高度积极的本科生聚集在一个活跃的研究小组中，并向他们介绍智力上的兴奋。这将使这些学生积极参与研究项目，帮助他们独立思考，培养创造力，培养在研究项目中工作所需的信心和技能，并在他们选择的职业道路上取得成功。它还将为他们提供接触强大导师的机会，并有机会开始与他们的同学和研究小组的前辈发展他们的网络。本REU网站旨在实现三个不同的目标：1)提供对大数据分析和机器学习概念的更深入理解；2)提高对数据分析和机器学习的热情和研究技能，并在本科教育期间向学生灌输专业技能和道德行为，特别是那些来自代表性不足的群体和/或在其本国机构中获得这项研究的机会有限的学生；3)提供国际研究经验，为全球STEM/精通数据的劳动力做好准备。该项目将支持30名本科生（为期三年）进行为期10周的高影响力研究实习经历。在此研究实习期间，参与者将在南美实力雄厚的研究机构智利大学（UCHILE）获得为期4周的大数据和机器学习项目的国际研究经验。该项目将招募来自全国任何STEM学科的学生。具体来说，将努力从包括女性在内的代表性不足的人群中招募至少50%的参与者，至少三分之一来自北达科他州以外，至少60%来自NDSU以外。本项目将向本科生介绍大数据和机器学习工具的独特应用，以管理数字工程系统。学生将加深对这些新概念的理解，并推进新的模型/算法，以解决能源基础设施、网络制造、精准农业和其他一些网络物理系统等行业的工程问题。最后，学生将学习理论和实践，以更好地解决实际工程问题，并展示其在现实生活场景中的应用。国际研究经验将进一步使这些学生通过获得全球研究和文化经验，加入全球劳动力。该项目由工程教育和中心部（工程理事会）以及促进竞争研究的既定计划（EPSCoR）共同资助。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。