Quality and Productivity Research Conference - Data and Science Is a Winning Alliance

该项目资助学生参加2019年6月11日至13日在华盛顿由美国大学主办的第36届质量和生产力研究会议（QPRC）。本次QPRC有一个特别的主题，致力于数据革命，“数据和科学是一个双赢的联盟。该会议旨在展示和探索数据与科学之间的相互作用，并讨论处理大型，多维，非结构化数据的现代科学方法。 会议将讨论数据和科学这两个基本知识来源如何相互利用，以加速发现并提高质量和生产力。 该计划将包括对数据科学各个方面的尖端现代方法的全面讨论，以及在流数据挖掘，机器学习，功能数据分析，图像重建和面部识别等计算机密集型领域取得的当前进展。 与会的统计学家、数据科学家、定量分析师以及不同行业和政府部门的代表将交流新的想法，分享利用现代大数据发现知识并将其应用于众多领域的经验。第36届QPRC的全体会议和邀请论文会议计划在以下主题中进行：机器学习，应用数据挖掘，时间序列和预测，文本分析，数据科学，网络安全，数据可视化，大数据分析，统计过程控制监控，功能数据分析和空间数据科学。 会议还包括投稿和海报会议以及技术参观。在此之前，有一个为期一天的课程“大数据分析：处理结构化、半结构化和非结构化数据”。“学生的强烈参与是第36届QPRC的重要组成部分。将努力扩大参与，从代表性不足的群体中招募学生，并吸引来自美国各地众多大学和研究生课程的学生。学生们被邀请提交贡献和海报演示文稿，并竞争旅行奖学金。会议的详细信息在其网站上，https://www.american.edu/cas/qprc/.This奖反映了NSF的法定使命，并被认为值得通过使用基金会的知识价值和更广泛的影响审查标准进行评估来支持。

This project funds student participation in the 36th Quality and Productivity Research Conference, or QPRC, hosted by American University in Washington, DC on June 11-13, 2019. This QPRC has a special theme devoted to the Data Revolution, "Data and Science Is a Winning Alliance." The conference aims to demonstrate and explore the interplay between data and science, and to discuss modern scientific approaches to handling big, multidimensional, unstructured data. The sessions will address how data and science, the two fundamental sources of knowledge, are leveraging each other to accelerate discoveries and increase quality and productivity. The program will include a comprehensive discussion of cutting-edge modern methodologies in diverse aspects of data science and current progress made in such computer-intensive fields as stream data mining, machine learning, functional data analysis, image reconstruction, and facial recognition. Participating statisticians, data scientists, quantitative analysts, and representatives of different branches of industry and government will exchange novel ideas and share experiences in working with modern big data to discover knowledge and applying it in numerous fields. Plenary and invited paper sessions at the 36th QPRC are scheduled in the following subjects: machine learning, applied data mining, time series and forecasting, text analytics, data science, cybersecurity, data visualization, big data analytics, statistical process control monitoring, functional data analysis, and spatial data science. The conference also includes contributed and poster sessions and a technical tour. It is preceded by a one-day course "Big Data Analytics: Dealing with Structured, Semi-structured, and Unstructured Data." Strong student participation is a vital component of the 36th QPRC. Efforts will be made to broaden participation by recruiting students from under-represented groups and engaging students from numerous universities and graduate programs across the United States. Students are invited to submit contributed and poster presentations and compete for travel scholarships. The conference details are on its web site, https://www.american.edu/cas/qprc/.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.