RET Site: Research Experiences for Teachers in Biologically-inspired Computing Systems

这笔资金在南阿拉巴马大学建立了一个新的教师研究经验(RET)网站。来自莫比尔和鲍德温县公立学校的在职初中和高中教师每年夏天将花六周时间从事以生物启发计算为重点的研究活动。RET教师将由南阿拉巴马大学的一个跨学科教员小组以及行业合作伙伴指导，在神经形态系统领域进行基于发现的研究项目，这是一种支持机器学习应用的生物启发系统。RET教师将设计符合标准的课程模块，他们将在学年期间在课堂上实施这些模块，并为其他教师举办讲习班。教师们还将在暑期研究活动和学年期间参加许多专业发展活动。这个项目应该在大学、K-12学校和周围社区之间建立持久的关系，帮助在大学和其他合作伙伴支持的学校建立强大的教育基础。RET网站由一个引人注目的计算和工程研究领域--神经形态系统--支撑。这些研究项目涉及支持未来计算系统的应用、架构、电路和设备。这些项目建立在教师导师的专业知识和持续研究的基础上。要研究的技术领域包括用于癌症检测的新的图像采集技术和图像处理算法，图像数据的尖峰神经网络算法，新的高能效存储结构和电路以支持已开发的算法，以及新的基于忆阻器件的神经形态系统设计，以实现更好的预测和精度。这项研究将为教师提供开发数学、物理、生物、化学、工程和技术方面的创造性课程模块，使其与州和国家课程标准保持良好一致。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 funding establishes a new Research Experiences for Teachers (RET) Site at the University of South Alabama. In-service middle school and high school teachers from Mobile and Baldwin County Public Schools will spend six weeks each summer engaged with research activities focused on biologically-inspired computing. The RET teachers will be guided by an interdisciplinary group of faculty from the University of South Alabama as well as industry partners on discovery-based research projects in the area of neuromorphic systems, biologically-inspired systems to support machine learning applications. The RET teachers will design standards-compliant curriculum modules which they will implement in their classrooms during the academic year and conduct workshops for other teachers. The teachers will also participate in many professional development activities during the summer research activity and the academic year. This project should develop a lasting relationship between the university, the K-12 schools, and the surrounding community that can help to build a strong educational foundation in the schools supported by the university and the other partners.The RET site is anchored by a compelling computing and engineering research area, neuromorphic systems. The research projects span applications, architecture, circuits, and devices that enable future computing systems. The projects build on the expertise and on-going research of the faculty mentors. The technical areas to be investigated include novel imagery collection techniques and image processing algorithms for cancer detection, spiking neural network algorithms for imagery data, new power-efficient memory architecture and circuits to support the algorithms that are developed, and new memristor device-based neuromorphic system design for better prediction and accuracy. The research will provide teachers around for developing creative course modules in mathematics, physics, biology, chemistry, engineering, and technology that align well with state and national curriculum standards.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.