EXTREEMS-QED: GW Mathematics and Statistics Training, Education, & Research (MASTER)

乔治华盛顿大学数学与统计培训、教育和研究(硕士)项目旨在激发学生对分析大规模数据的计算挑战背后的数学问题和技术的兴趣。该项目将由数学系和统计系运营，并得到计算机科学系的支持。计算与数据支持的科学与工程(CDS&amp；E)现已成为一门独特的智力和技术学科，位于应用数学、统计学、计算机科学、核心科学和工程学科的交叉点上。该项目将帮助那些准备好迎接CDS&E新挑战的数学和统计本科生，培养学生在使用大数据的同时进行数学思维，这将被证明对学生在许多应用领域的成功职业生涯有用。该项目将包括课程改进、研究指导和教师发展。课程改进将增加以CDS&A；E；为主题的新课程；本科生研究指导计划将为数学或统计专业的有才华的本科生提供研究经验。这些研究项目本身将涉及CDS&E研究问题，这些问题来自网络动力学、生物数据分析、集群、大数据集的拓扑结构和压缩传感。将开设的新课程包括网络数学、数据勘探统计和CDS&A；E数学建模；这些课程将侧重于各种主题，包括网络数据分析、生物网络数据、数据勘探的图形技术、统计计算、维度分析和大型数据集的建模。为教师举办的暑期讲习班将提高大学教师在CDS和E方面的技能。

The George Washington University Mathematics and Statistics Training, Education, and Research (MASTER) program is designed to excite students about the mathematical questions and techniques underlying the computational challenges of analyzing large-scale data. The program will be run by the Departments of Mathematics and Statistics, with support from faculty in Computer Science. Computational and Data-enabled Science and Engineering (CDS&E) has now emerged as a distinct intellectual and technological discipline lying at the intersection of applied mathematics, statistics, computer science, core science and engineering disciplines. The program will help educate mathematics and statistics undergraduate students who are prepared to confront new challenges in CDS&E. Training students to think mathematically while working with big data will prove useful for students' successful careers in many application areas.The project will feature curricular enhancements, research mentoring, and faculty development. The curricular enhancements will add new courses centered about the theme of CDS&E; the undergraduate research mentoring program will provide research experience for talented undergraduates majors in mathematics or statistics. The research projects will themselves involve CDS&E research questions arising from network dynamics, biological data analysis, clustering, topology of large data sets, and compressive sensing. Among the new courses to be offered are mathematics of networks, the statistics of data exploration, and CDS&E mathematical modeling; the courses will be focused on the variety of topics, including network data analysis, biological network data, graphical techniques for data exploration, statistical computing, dimension analysis, and modeling of large data sets. Summer workshops for faculty will enhance the skills of college faculty in CDS&E.