Workshop: Transforming Civil & Environmental Engineering Curriculum: Big Data, Machine Learning, and AI Innovations Impact on CEE Education; Alexandria, Virginia; 10 December 2

研讨会：土木工程转型

• 批准号: 1908926
• 负责人: Lucio Soibelman
• 金额: $ 5.5万
• 依托单位: University of Southern California
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-11-15 至 2020-04-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1908926&HistoricalAwards=false
• 关键词: Workshop; Transforming; Civil; & Environmental

Over the last several years, research and development on Machine Learning, Big Data, and Artificial Intelligence has demonstrated many opportunities for creating novel concepts, applications, tools and systems with lasting and transformative impacts on nearly every industry and economic sector. As Civil and Environmental Engineers adopt new computer technologies, computerized data are becoming more and more available. There exist numerous opportunities to exploit and extract knowledge from this vast amount of data through the development of frameworks and algorithms that support the acquisition, modeling, management, and analysis of such diverse infrastructure-oriented data. With sensors everywhere, the field of Civil and Environmental Engineering is undergoing transformative changes in the physical and natural systems we live in and travel through. The massive (big) data generated from these sensors presents tremendous opportunities for a wide range of possibilities that could only be imagined before. Consequently, Civil and Environmental engineers who have traditionally relied upon small data (generated through experiments, surveys, and labs etc.) face novel challenges in utilizing the newly-generated big data to fully exploit opportunities. This workshop will convene a diverse group of participants from universities, industry and stakeholders in civil and environmental engineering, computer science, machine learning, data analytics and artificial intelligence to chart a course of action to enable the transformation of Civil and Environmental Engineering (CEE) curricula and fully prepare the CEE community for both the opportunities and challenges brought by sensors everywhere, internet of things devices, and the massive amount of resulting data. The workshop will seek to deliver the following specific impacts to CEE departments and to the research community: (1) Provide insight into the current availability of expertise on big data, machine learning, and artificial intelligence within Civil and Environmental Engineering departments; (2) Enhance understanding of the emerging educational needs for different areas of expertise within Civil and Environmental Engineering related to big data, data analytics, machine learning, and artificial intelligence; (3) Guide Civil and Environmental Engineering departments in aligning their curriculum with current needs for the profession; (4) Provide the leadership and guidance for the future development of machine learning, big data, and artificial intelligence tutorial modules specifically aligned to Civil and Environmental Engineering curriculum needs. At a broader level, it is intended that the workshop output will serve as a beacon for bringing advanced computing techniques to Civil and Environmental Engineering, as well as other Engineering disciplines, supporting novel curriculum development. The workshop will provide a roadmap and the leadership for the development of the required tools that will enhance the capabilities of future engineering graduates enhancing competitiveness of the engineering profession and improving engineering education.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.

在过去的几年里，机器学习、大数据和人工智能的研究和开发已经证明了创造新概念、应用程序、工具和系统的许多机会，这些新概念、应用程序、工具和系统对几乎每个行业和经济部门都有持久和变革性的影响。随着土木和环境工程师采用新的计算机技术，计算机化的数据变得越来越可用。存在许多机会来通过开发框架和算法来从这些大量的数据中利用和提取知识，这些框架和算法支持对这些不同的面向基础设施的数据的获取、建模、管理和分析。随着传感器无处不在，土木与环境工程领域正在我们生活和旅行的物理和自然系统中发生变革。这些传感器产生的大量（大）数据为以前只能想象的各种可能性提供了巨大的机会。因此，传统上依赖于小数据（通过实验，调查和实验室等生成）的土木和环境工程师。在利用新产生的大数据充分利用机遇方面面临新的挑战。本次研讨会将召集来自大学，工业和土木与环境工程，计算机科学，机器学习，数据分析和人工智能利益相关者的多元化参与者，制定行动方针，以实现土木与环境工程（CEE）课程的转型，并为CEE社区做好充分准备，以应对传感器无处不在带来的机遇和挑战。物联网设备，以及由此产生的大量数据。该研讨会将寻求为中东欧部门和研究界带来以下具体影响：（1）深入了解土木和环境工程部门内大数据，机器学习和人工智能专业知识的当前可用性;（2）加强对与大数据相关的土木和环境工程中不同专业领域的新兴教育需求的理解，数据分析，机器学习和人工智能;（3）指导土木和环境工程部门将其课程与当前的专业需求相一致;（4）为机器学习，大数据和人工智能教程模块的未来发展提供领导和指导，特别是与土木和环境工程课程需求相一致。在更广泛的层面上，它的目的是，研讨会的输出将作为一个灯塔，使先进的计算技术，土木和环境工程，以及其他工程学科，支持新的课程开发。该研讨会将为开发所需工具提供路线图和领导力，这些工具将提高未来工程专业毕业生的能力，增强工程专业的竞争力，并改善工程教育。该奖项反映了NSF的法定使命，并被认为值得通过使用基金会的智力价值和更广泛的影响审查标准进行评估来支持。