Brigham Young University Planning Grant: I/UCRC for Center for Visual and Decision Informatics

杨百翰大学规划资助：I/UCRC 视觉与决策信息学中心

• 批准号: 1650579
• 负责人: Christophe Giraud-Carrier
• 金额: $ 1.4万
• 依托单位: Brigham Young University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-02-01 至 2018-01-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1650579&HistoricalAwards=false
• 关键词: Brigham; Young; University; Planning; Grant

This award seeks to assist Brigham Young University (BYU) in joining the Center for Visual and Decision Informatics (CVDI), an existing Industry University Cooperative Research Center (IUCRC). The CVDI Center is currently made up of the University of Louisiana at Lafayette, Drexel University, and Tampere University of Technology. BYU will use this award to plan and prepare for the establishment of the new site by hosting informational meetings for potential partners about the benefits of membership in CVDI and the mechanics of the Center, attend the scheduled CVDI's Industry Advisory Board meeting in April 2017, and prepare a joint industry and university research agenda around the expertise of the site and the needs/interests of industry partners. BYU will leverage its big data capstone class, where industry partners pitch their projects to the students who then vote on their preferred projects and form groups that are mentored throughout by company personnel. Through external partners' mentoring, students are exposed to the realities of data analytics and gain experience and skills that cannot be found in a strictly academic setting. This, in turn, can prepare students for the workforce and improves their ability to be effective contributors to science and engineering.

该奖项旨在协助杨百翰大学（BYU）加入现有行业大学合作研究中心（IUCRC）的视觉和决策信息中心（CVDI）。 CVDI中心目前由路易斯安那大学拉斐特大学，德雷克塞尔大学和坦佩雷技术大学组成。 BYU将通过该奖项来计划和准备建立新网站，通过为潜在的合作伙伴举办有关CVDI成员资格和中心机制的收益的信息会议，参加了2017年4月的CVDI行业顾问委员会会议，并准备联合行业和大学研究项目，围绕该地点的专业知识以及行业群体的需求/利益。 BYU将利用其大数据帽级课程，行业合作伙伴将其项目推向学生，然后他们对他们的首选项目和组成组进行投票，这些项目由公司人员进行了指导。通过外部合作伙伴的指导，学生接触到数据分析的现实，并获得在严格的学术环境中找不到的经验和技能。反过来，这可以使学生为劳动力做准备，并提高他们成为科学和工程学有效贡献者的能力。