REU Site: Research Projects in Data-Enabled Industrial Mathematics

这个位于安柏瑞德航空大学的REU站点每年为10名本科生提供机会，在2021-2023年夏季参与数据支持工业数学的真实研究项目。这种独特的研究经验的目的是为学生准备在数据驱动的数学挑战，并为他们提供技能，在当今的数据丰富的世界导航能力。学生将学习将商业、工业或政府提出的技术、组织和数据问题转化为可解决的数学问题。该项目将招收女性、少数族裔、经济困难学生、第一代大学生等不同群体的优秀学生。参与将使对工业数学研究感兴趣的学生具备对数据分析，数学建模和解决问题的能力以及有效的沟通技巧的深刻理解。每个研究项目的进展和结果的视频纪录片将被用来促进本科生的研究和更广泛的受众的数据素养。这个网站的最终理念是模拟现实世界的工业研究经验，关注学生的成长，鼓励学生在课堂之外的层次上与教育材料互动。学生们将合作解决由企业、政府和工业直接提供的问题。教师导师和行业合作伙伴的两个视角是这种独特体验的关键：教师导师明确关注项目核心的数学和数据科学方面，而行业合作伙伴则提供相关行业需求和背景的激励。学生将通过实例学习数据科学技能如何在实际应用中发挥关键作用，这种经历将促进明智的职业决策和促进专业发展。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。

This REU site at Embry-Riddle Aeronautical University provides ten undergraduate students each year with opportunities to participate in authentic research projects in data-enabled industrial mathematics during the summers 2021-2023. The objectives of this unique research experience are to prepare students for challenges in data-driven mathematics and to provide them with skills to navigate capably in today’s data-rich world. Students will learn to transform technical, organizational, and data-enabled problems posed by business, industry, or government into solvable mathematical questions. The program will recruit talented students from diverse groups, including females, underrepresented minorities, financially disadvantaged students, and first-generation college students. Participation will equip students interested in industrial mathematics research with a strong understanding of data analytics, mathematical modeling and problem-solving abilities, and effective communication skills. Video documentaries of the progress and results of each research project will be used to promote undergraduate research and data literacy for a broader audience. The ultimate idea of this site is to model real-world industrial research experiences, focusing on student growth and encouraging students to interact with the educational material at a level that goes beyond a classroom setting. The students will work collaboratively on problems provided directly by business, government, and industry. The two perspectives of the faculty mentor and of the industrial partners are keys to this unique experience: the faculty mentor maintains a clear focus on the mathematics and data science aspects at the core of the project, while industrial partners provide an incentive of relevant industrial needs and contexts. Students will learn through examples how data science skills can be critical for practical applications, and the experience will foster informed career decisions and promote professional development.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.