Statistics in the Big Data Era

大数据时代的统计

• 批准号: 2005243
• 负责人: Peng Ding
• 金额: $ 2万
• 依托单位: University of California-Berkeley
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-01-01 至 2022-12-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2005243&HistoricalAwards=false
• 关键词: Statistics; Big; Data; Era

This award supports participation by graduate students and junior researchers in the conference "Statistics in the Big Data Era" held at the Simons Institute for the Theory of Computing at the University of California, Berkeley during May 27-29, 2020. This conference focuses on the changing role and nature of the discipline of statistics in the time of a data deluge in many applications, and on the increasing success of artificial intelligence at performing many data analysis tasks. The conference will feature approximately twenty invited speakers who have made fundamental contributions to the theory and practice of statistics and machine learning. The meeting aims to bring together experts in statistical methodology and theory for complex and big data with researchers focused on a range of applications, from genomics to social networks, and to provide opportunities for early-career researchers to learn about both emerging methods and applications. This conference will be an especially important opportunity for graduate students and early-career researchers to see recent advances and emerging challenges in the theory, methodology, and application of statistics in the big data era.Statistics plays a central role in quantitative research in many disciplines, including social and biological sciences. With the advances in information technology, statistics has gone through a paradigm shift from conventional methods to big data analytics and modern machine learning. This conference will bring together current leading statisticians and the next generation of statistical leaders to discuss achievements and difficulties in the statistical analysis of big data. The meeting will focus on methodology for solving challenges involving big data with complex and heterogeneous structure. The discussions will promote opportunities for statisticians to identify important research topics and critical applications in science and industry. Another important component is a poster session in which students and early-career researchers present their work. The conference program also includes discussion of statistics and data science education in the era of big data.More information about the conference can be found at https://simons.berkeley.edu/workshops/statistics-big-data-era.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.

该奖项支持研究生和初级研究人员参加2020年5月27日至29日在加州大学伯克利分校西蒙斯计算理论研究所举行的“大数据时代的统计”会议。本次会议的重点是在许多应用程序中数据泛滥的时代，统计学科的角色和性质的变化，以及人工智能在执行许多数据分析任务方面的日益成功。会议将邀请大约20位对统计和机器学习的理论和实践做出重要贡献的演讲者。会议旨在将复杂和大数据统计方法和理论方面的专家与专注于从基因组学到社交网络等一系列应用的研究人员聚集在一起，并为早期职业研究人员提供学习新兴方法和应用的机会。本次会议将为研究生和早期职业研究人员提供一个特别重要的机会，让他们了解大数据时代统计学理论、方法和应用方面的最新进展和新挑战。统计学在许多学科的定量研究中发挥着核心作用，包括社会科学和生物科学。随着信息技术的进步，统计学经历了从传统方法到大数据分析和现代机器学习的范式转变。本次会议将汇集当前领先的统计学家和下一代统计领导人，讨论大数据统计分析的成就和困难。会议将重点讨论解决涉及复杂和异构结构的大数据挑战的方法。这些讨论将促进统计人员有机会确定科学和工业领域的重要研究课题和关键应用。另一个重要组成部分是海报会议，学生和早期职业研究人员介绍他们的工作。https://simons.berkeley.edu/workshops/statistics-big-data-era.This奖项反映了NSF的法定使命，并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，被认为值得支持。