Collaborative Research: CyberTraining: Implementation: Small: CITY-AI: CyberTraining for AI-Enabled Intelligent Urban Informatics and Smart City Innovation

Cities are increasingly generating large-scale and real-time data from sensors, transportation systems, satellites, and mobile devices. These data, combined with advances in cyberinfrastructure and Artificial Intelligence (AI), provide new opportunities for timely, precise, and data-driven urban management in areas such as transportation, infrastructure management, public health, urban sensing, and emergency response. However, many students, researchers, educators, and practitioners in urban-related fields, including geography, urban planning, and the broader social sciences, lack the cyberinfrastructure, AI, and data analytics skills needed to fully use these emerging resources. To address this gap, this project will establish CyberTraining for AI-Enabled Intelligent Urban Informatics and Smart City Innovation (CITY-AI) to develop the necessary skills in the urban informatics workforce through curriculum and training materials. The CITY-AI project will introduce advanced cyberinfrastructure, AI, and data analytics to urban informatics communities by developing a cyberinfrastructure-enabled urban informatics curriculum. Specifically, the project will develop and deliver 16 training modules and organize webinars, workshops, and summer schools to train more than 1,500 students, researchers, educators, and practitioners. The curriculum is organized around four connected components: 1) the Core Cyberinfrastructure Skills component introduces cyberinfrastructure and high-performance computing, helping participants access national computing resources, run batch workflows, and execute containerized Python and Jupyter Notebook workflows; 2) the Urban Data Analytics component focuses on developing data analytics skills for emerging forms of urban data, including fine-grained spatiotemporal, large-scale, and streaming data; 3) the Urban Informatics Use-Cases component applies these skills to real-world urban problems including air quality, urban heat, and transportation using cyberinfrastructure-enabled AI workflows; and 4) the Urban Informatics in Action component supplements the training modules through webinars series that connect these concepts to real-world problem-solving with urban big data. All CITY-AI training materials will be openly accessible and hosted as executable and reproducible Jupyter notebooks on national cyberinfrastructure platforms, ensuring broad and lasting access beyond the project period. This award by the Office of Advanced Cyberinfrastructure is jointly supported by the Section of Civil, Mechanical, and Manufacturing Innovation in the Directorate for Engineering. 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.