PARTNER: Expand AI2ES for 4D space-time organization of precipitation processes and extremes, visualization tools, and workforce development

该项目是圣地亚哥州立大学、加州大学欧文分校和人工智能天气、气候和沿海海洋学值得信赖的人工智能研究所(AI2ES)之间的扩展人工智能合作伙伴关系。在这个项目中，两个为少数群体服务的机构与一家人工智能研究所合作，领导新的活动，专注于扩大其机构已经建立的人工智能研究和教育项目，并围绕发展人工智能寻求共同、互补的目标，同时考虑到对社会的使用，以及培养下一代人工智能教育和劳动力人才。该项目还将在以前没有很好开展此类活动的地方建立社区和新的人工智能卓越中心。ExpAI2ES项目扩大了两个拉美裔服务机构(HSI)的研究、教育活动和劳动力发展。这些组织与AI2ES合作，在人工智能基础研究和环境科学的人工智能应用方面领导合作伙伴关系。ExpAI2ES的研究重点是降水和其他大气变量的时空组织和多尺度结构的人工智能建模，特别强调极值和不确定性量化。该研究还开发了4维数据可视化工具，如4维可视交付(4DVD)软件，可以支持大气科学和人工智能进步教育教学法的更广泛应用。这些研究和教育进展将有效应对气候变化、环境可持续性以及代价高昂的极端天气和灾害方面的迫在眉睫的挑战，同时吸引多样化和尚未开发的人才库。该项目将建立的大气科学进步教育(PEAS)框架将有助于开发新的课程材料，并改善相关机构的人工智能课程的教育内容。该项目新颖的“豌豆+人工智能”教育框架将进一步扩展到对学校教师的培训，他们可以与学生一起使用拟议的4DVD技术来实现气候数据的可视化和发现。与真实环境数据相结合，结合基于现代视频的4DVD人工智能工具，将激励学生在STEM职业生涯中致力于气候科学和环境可持续发展的紧迫问题。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。

This project is an ExpandAI Partnership between San Diego State University, the University of California Irvine, and the AI Institute for Research on Trustworthy AI in Weather, Climate and Coastal Oceanography (AI2ES). In this project, two minority-serving institutions collaborate with an AI Institute to lead new activities focused on scaling up already-established AI research and education programs at their institutions and to pursue shared, complementary goals around developing AI with use for society in mind and for developing the next generation of AI education and workforce talent. The project will also build community and new centers of excellence in AI where such activities were not previously well developed. The ExpAI2ES project expands research, educational activities, and workforce development in two Hispanic-Serving Institutions (HSI). In collaboration with AI2ES, these organizations lead a partnership in AI basic research and AI applications to environmental science. The research focus of ExpAI2ES is on AI modeling of the space-time organization and multiscale structure of precipitation and other atmospheric variables, with special emphasis on extremes and uncertainty quantification. The research also develops 4-dimensional data visualization tools, such as the 4-dimensional visual delivery (4DVD) software, that can support a wider application of progressive education pedagogy for atmospheric sciences and AI. These research and educational advances will effectively address imminent challenges in climate change, environmental sustainability, and costly weather extremes and hazards, while engaging a diverse and untapped pool of talent. The Progressive Education for Atmospheric Science (PEAS) framework to be established in this project will help develop new course material and improve the educational offerings of AI courses for relevant institutions. The project’s novel “PEAS+AI” educational framework will be further extended to the training of school teachers who together with students can use the proposed 4DVD technology for climate data visualization and discovery. The engagement with real environmental data combined with the modern video-based 4DVD AI tools will inspire students towards STEM careers to work on the pressing problems of climate science and environmental sustainability.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.