CISE Minority Institutions Infrastructure: Building an Academic Pipeline for Miniority Scholars

9633299 Hiromoto，Robert Boppana，Rajendra 德克萨斯大学-圣安东尼奥分校 CISE少数民族机构基础设施：为少数民族学者建立学术管道 该项目建立了一个少数民族学生的管道，重点是通过适当的财政支持和辅导活动留住合格的本科生和研究生。 目标是让学生直接参与正在进行的教师研究项目，从而为研究生学习和研究项目做好准备。 参与该计划的少数民族研究生将帮助教师指导本科生，除了他们自己的学习和研究义务。 该项目包括两个主要目标，旨在改善少数民族学生准备研究生课程的管道。 第一个目标是积极招募和发展对计算机科学感兴趣的少数民族学生，通过提供大学预科和低年级本科水平的预备培训，辅导和指导。 第二个目标是为高年级和研究生提供资金支持，并增加对教师研究的参与，以提高少数民族的保留率和研究生入学率。 学生将在五个重要领域内参与教师研究： 1)并行和分布式算法设计，用于高性能 科学计算 2)软件可视化和程序执行监控; 3)并行编译技术; 4)网络路由和调度算法; 5)并行和分布式仿真技术。

9633299 Hiromoto, Robert Boppana, Rajendra University of Texas - San Antonio CISE Minority Institutions Infrastructure: Building an Academic Pipeline for Minority Scholars This project builds a pipeline of minority students, focusing on the retention of qualified undergraduate and graduate students by appropriate financial support and mentoring activities. The goal is to involve students directly in ongoing faculty research projects and thus prepare them for graduate studies and research programs. Graduate minority students involved in the program will help faculty in mentoring undergraduates, in addition to their own studies and research obligations. The project encompasses two main thrust designed to improve the pipeline of minority students prepared for graduate programs. The first goal is to aggressively recruit and develop minority students interested in computer science by providing preparatory training, tutoring, and mentoring at the pre-college and lower-division undergraduate levels. The second goal is to provide upper-division and graduate students with funding support and increased involvement in faculty research in order to improve minority retention and graduate enrollment. Students will be involved in faculty research within five important areas: 1) parallel and distributed algorithm design for applications in high-performance scientific computing 2) software visualization, and program execution monitoring; 3) parallel compiler technology; 4) network routing and scheduling algorithms; 5) parallel and distributed simulation techniques.