CC* CIRA: Mid-TN AI for Interdisciplinary Imaging Interpretation Alliance

该项目促进了田纳西州中部以人工智能(AI)为中心的新的地区性合作。这些规划和协调项目的一个主要目标是，通过举办社区活动、为学生举办培训和辅导讲习班以及共享教学和研究活动的计算资源，促进注重研究的机构与为少数群体服务的机构之间的联系。通过中TN人工智能跨学科成像解释联盟(AI4A)，该项目确定、表征并支持成像人工智能科学的驱动因素以及跨AI4A的此类科学能力。该项目的一个关键组成部分是发展人力基础设施和互联。AI4A举办暑期教师奖学金，以促进合作，并提供暑期学生机会，与现有的REU项目(如Fisk Bridge NSF REU)合作，与博士前实习生接触。AI4A为人工智能成像所需的技术技能开发培训材料，包括GPU计算、深度学习概念和实践，以及高性能计算的当前计算环境。AI4A还提供对这些设备和环境的访问，以支持研究协作，并为学生提供开发和验证大型模型的实践经验。该项目促进了新的研究方向的出现，但基于参与者目前的研究重点，并基于放射学、神经学和神经科学、细胞显微镜、生态学和遥感、交通、材料工程、考古学、数字人类学和深层网络等领域的成像问题。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 facilitates new regional collaborations in middle Tennessee centered on artificial intelligence (AI) for imaging. A primary goal of these planning and coordination project is to facilitate connections between research-focused institutions and minority serving institutions by hosting community events, training and tutorial workshops for students, and sharing computational resources for both pedagogy and research activities. Through the Mid-TN AI for Interdisciplinary Imaging Interpretation Alliance (AI4A), the project identifies, characterizes, and enables drivers of imaging AI science and the capacity for such science across the AI4A.A critical component of this project is the development of human infrastructure and interconnections. AI4A hosts summer faculty fellowships to seed collaborations, and summer student opportunities to engage with pre-doctoral trainees in collaboration with existing REU programs such as the Fisk Bridge NSF REU. AI4A develops training materials for the technical skills required in AI-imaging, including GPU computing, deep learning concepts and practice, and current computing environments for high performance computing. AI4A also provides access to these devices and environments to support research collaborations and to provide practical experience for students in the development and validation of large models. The project facilitates the emergence of de novo research directions, but based on the current research foci of participants, and based around imaging problems in radiology, neurology and neuroscience, cell microscopy, ecology and remote sensing, transportation, materials engineering, archeology, digital anthropology, and deep networks.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.