Planning: HBCU-UP: Strengthening Data Science Research Capacity and Education Programs through Academia-Industry Partnership

历史上的黑人学院和大学本科项目(HBCU-UP)为加强HBCU的STEM本科教育和研究提供了支持。为了填补学术界和产业界在数据科学领域的空白，佛罗里达农工大学-佛罗里达州立大学(FAMU-FSU)工程学院的项目团队将与美国航空公司(AA)的运筹学和高级分析(ORAA)小组合作，在数据科学研究和教育方面开发一个学术界和产业界合作的模式。研究和教育领域的项目活动旨在使对从事与数据科学相关的职业感兴趣的本科生和研究生受益。FAMU-FSU工程学院现有的工业工程课程预计将得到加强，特别是两门核心课程，即工程大数据分析和机器学习导论。该项目还将支持学院研究人员将他们的研究范围扩大到航空，这是一个对繁荣和竞争力至关重要的行业。该项目将追求以下具体目标：(1)为本科生和研究生设计和推出以航空数据分析为重点的年度案例竞赛；(2)通过行业主导和以学生为中心的指导和职业发展培训，为未被充分代表的工程学学生创建一条航空数据科学途径；以及(3)通过研究生、工程学教师和行业专业人员的共同努力，利用先进的数据分析来推动航空公司运营的实践。在成功解决了几个关键研究课题后，机器学习和数学规划将在机器学习和数学规划方面做出一些方法论上的贡献，这些主题包括飞行水平的托运行李预测、飞机配置和负载规划以及备件的长期需求预测等。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。

The Historically Black Colleges and Universities - Undergraduate Program (HBCU-UP) provides support to strengthen STEM undergraduate education and research at HBCUs. To fill a gap between academia and industry in the field of data science, the project team at the Florida A&M University-Florida State University (FAMU-FSU) College of Engineering will develop an academia-industry partnership model in data science research and education in collaboration with the Operations Research and Advanced Analytics (ORAA) Group at American Airlines (AA). The project activities across research and education are designed to benefit both undergraduate and graduate students who are interested in pursuing a career related to data science. The existing industrial engineering curriculum at the FAMU-FSU College of Engineering is expected to be strengthened, especially two core courses, namely Big Data Analytics in Engineering and Introduction to Machine Learning. This project will also support faculty investigators in expanding their research portfolio to aviation, a sector critical to the prosperity and competitiveness.The following specific objectives will be pursued under this project: (1) To design and launch an annual case competition focusing on aviation data analytics for undergraduate and graduate students; (2) To create an aviation data science pathway for underrepresented engineering students through industry-led and student-centered mentoring and professional development training; and (3) To advance the practice of airline operations through joint efforts by graduate students, engineering faculty, and industry professionals, using advanced data analytics. A few methodological contributions in machine learning and mathematical programming would be made after successfully addressing a few key research topics on prediction of checked baggage at flight level, aircraft configuration and load planning, and long-term demand prediction for spare parts, among others.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.