REU Site: REUMass: A Summer Computing Research Experience in Data Science

标题：REU网站：REUMass：数据科学的夏季计算研究经验这个项目为本科生提供了为期10周的密集夏季研究经验，重点是数据科学，这是一个具有高社会影响和显著学生兴趣的新兴领域。数据科学研究能够从大量数据中有效提取知识的理论和方法。这个项目的智力价值包括调查和开发新的数据分析方法，改进分析基础设施的方法，以及将这些分析方法和基础设施应用于有用的问题。该项目更广泛的意义和重要性包括增加计算机科学研究生学习对社区学院和代表性不足群体的学生的吸引力，并增加这些学生对数据科学的技术知识。每个学生项目都是围绕单一类型的分析方法、基础设施或应用程序进行的，但项目嵌入在数据科学的集成“深度堆栈”视图中，将应用程序与分析和基础设施连接起来。学生们参加了许多技术活动（研讨会、专题讨论会、实地考察等）和社会活动，这些活动已被证明成功地在过去一年的参与者之间建立了密切和持续的关系。这一重点有助于强调基础计算机科学如何使广泛的信息技术应用成为可能，并显示了计算机科学中机会的广度，这些领域已被证明对提案的目标群体具有吸引力。

Title: REU Site: REUMass: A Summer Computing Research Experience in Data ScienceThis project provides undergraduate students with a 10-week intensive summer research experience focused on data science, an emerging area with high societal impact and significant student interest. Data science studies theory and methods that enable efficient extraction of knowledge from large amounts of data. The intellectual merits of this project include the investigation and development of new methods for data analysis, methods for improving the infrastructure for analysis, and the application of those analysis methods and infrastructure to useful problems. The project's broader significance and importance include increasing the attractiveness of graduate study in computer science for students from community colleges and underrepresented groups, and increasing the technical knowledge of data science among such students.Each student project is oriented around a single type of analysis method, infrastructure, or application, but projects embed that work within an integrated "deep stack" view of data science that connects applications with analytics and infrastructure. Students participate in a number of technical activities (workshops, symposia, field trips, etc.) and social events that have proven successful in creating a close and sustained relationship among the participants in past year's cohorts. This focus helps emphasize how fundamental computer science enables a broad set of information technology applications as well as showing the breadth of opportunities in computer science, and these areas have proven to be attractive to the proposal's target cohorts.