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研究所（AI2ES）在天气、气候和沿海海洋学领域的可信赖人工智能合作伙伴关系。在该项目中，两家少数民族服务机构与一家人工智能研究所合作，牵头开展新的活动，重点是扩大其机构内已经建立的人工智能研究和教育项目，并在开发人工智能方面追求共同的、互补的目标，以实现为社会服务的人工智能，并培养下一代人工智能教育和劳动力人才。该项目还将建立社区和新的人工智能卓越中心，这些活动以前没有得到很好的发展。ExpAI2ES项目扩大了两个西班牙裔服务机构（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人工智能在环境科学中的应用方面建立了伙伴关系。ExpAI2ES的研究重点是对降水等大气变量的时空组织和多尺度结构进行人工智能建模，特别注重极值和不确定性的量化。该研究还开发了四维数据可视化工具，如四维视觉传输（4DVD）软件，可以支持在大气科学和人工智能领域更广泛地应用渐进式教育教学法。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等迫在眉睫的挑战，同时吸引多样化和未开发的人才。在该项目中建立的大气科学进步教育（PEAS）框架将帮助开发新的课程材料，并为相关机构改善人工智能课程的教学内容。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，这些教师可以与学生一起使用拟议的4DVD技术进行气候数据可视化和发现。与真实环境数据的接触与现代基于视频的4DVD人工智能工具相结合，将激励学生从事STEM职业，致力于解决气候科学和环境可持续性等紧迫问题。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值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.