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

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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.