PARTNER: An AI/ML Collaborative for Southeast Florida Coastal Environmental Data and Modeling Center

该项目是佛罗里达国际大学（FIU）、北卡罗来纳州立大学（NCSU）、德克萨斯州a&m Corpus Christi大学（TAMU-CC）和人工智能研究所（AI Institute for Research on Trustworthy AI in Weather, Climate, and Coastal Oceanography, AI2ES）之间的扩展人工智能合作项目。在这个项目中，一个为少数民族服务的机构与另外两个MSIs和一个人工智能研究所开展了一项新的合作，重点是扩大其机构内已经建立的研究和教育项目，并在开发人工智能方面追求共同的、互补的目标，以造福社会，并培养下一代人工智能教育和劳动力人才。这项合作研究的重点是开发人工智能，以管理沿海人口众多地区面临的洪水破坏威胁和其他环境压力，重点是佛罗里达州东南部的环境影响。该项目还将围绕这个新的人工智能卓越中心建立社区，此前此类活动并未得到很好的发展。该项目在佛罗里达国际大学（FIU）建立了南佛罗里达海岸环境数据和建模中心，促进综合研究和教育工作，开发人工智能和机器学习技术，以理解和预测影响海洋、城市、农业和自然系统的关键过程，并研究对南佛罗里达重要的沿海环境问题。该区域包括生态敏感和经济重要的区域，如比斯坎湾，城市化走廊，与海湾接壤的支流流域，以及区域流域的地表水和地下水系统。由于财产价值高、人口密集、低洼地区脆弱，该地区极易受到洪水破坏和其他环境压力的影响，如海平面上升、城市洪水、水质监测和有害藻类爆发检测。该项目侧重于四个领域。首先，该中心管理和制作人工智能准备好的数据集，并公开提供用于测试人工智能/机器学习技术和开发解决方案的数据集。其次，研究人员合作开发可信赖的人工智能，以理解和预测沿海环境现象，包括开发基于物理的人工智能模型、可靠的人工智能系统和可解释的人工智能方法。第三，研究人员将人工智能/机器学习应用于南佛罗里达沿海环境问题的研究，如海平面变化、复合沿海洪水和有害藻类大量繁殖。最后，FIU和AI2ES为FIU在人工智能/机器学习和环境科学领域的本科生和研究生提供教育、培训和劳动力发展机会，包括开发本科跨学科项目，加强两年制学院学生的衔接项目，共享教育材料，促进研究交流，并通过实地考察、实习机会建立机构之间的联盟。以及跨机构的研讨会和研讨会。该项目部分由美国国家科学基金会的路易斯·斯托克斯少数民族参与联盟（LSAMP）项目资助，该项目隶属于STEM卓越平等部。”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 the Florida International University (FIU), North Carolina State University (NCSU), Texas A&M Corpus Christi (TAMU-CC), and the AI Institute for Research on Trustworthy AI in Weather, Climate, and Coastal Oceanography (AI2ES). In this project, a minority-serving institution leads a new collaboration with two other MSIs and an AI Institute focused on scaling up already-established 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 collaborative research focuses on the development of AI to manage threats of flood damage and other environmental stresses faced by areas with high coastal population, with an emphasis on environmental impacts in Southeast Florida. The project will also build community around this new center of excellence in AI where such activities were not previously well developed. This project establishes the South Florida Coastal Environmental Data and Modeling Center at Florida International University (FIU), promoting integrated research and education efforts to develop artificial intelligence and machine learning techniques for understanding and predicting the key processes affecting ocean, urban, agricultural, and natural systems, and for studying coastal environmental issues important to South Florida. This region encompasses ecologically sensitive and economically important areas, such as Biscayne Bay, urbanized corridors, tributary watersheds bordering the Bay, and the surface and groundwater systems in regional watersheds. Due to high property values, dense population, and vulnerable low-lying areas, the region is highly susceptible to flood damage and other environmental stresses such as sea-level rise, urban flooding, water quality monitoring, and harmful algae bloom detection. The project focuses on four areas. Firstly, the Center manages and makes curated datasets AI-ready and publicly available for testing AI/ML techniques and developing solutions. Secondly, the researchers collaborate on trustworthy AI for understanding and predicting coastal environmental phenomena, including developing physics-informed AI models, reliable AI systems, and explainable AI methods. Thirdly, the researchers apply AI/ML to study South Florida coastal environmental problems, such as sea-level variability, compound coastal flooding, and harmful algae blooms. Lastly, FIU and AI2ES provide education, training, and workforce development opportunities for diverse undergraduate and graduate students at FIU in AI/ML and Environmental Science, including developing an undergraduate interdisciplinary program, strengthening pathway programs for students from 2-year colleges, sharing education materials, and facilitating research exchange and building alliances among institutions via site visits, internship opportunities, and cross-institution workshops and seminars. The project is partially funded by NSF’s Louis Stokes Alliances for Minority Participation (LSAMP) program within the Division of Equity for Excellence in STEM.”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.