Recent Developments on Mathematical/Statistical Approaches in Data Science

数据科学中数学/统计方法的最新发展

• 批准号: 1821870
• 负责人: Yifei Lou
• 金额: $ 1.65万
• 依托单位: University of Texas at Dallas
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-03-01 至 2019-10-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1821870&HistoricalAwards=false
• 关键词: Recent; Developments; Mathematical; Statistical; Approaches; Recent; Developments; Mathematical; Statistical; Approaches

A workshop on Recent Developments on Mathematical/Statistical Approaches in Data Science will be held at the University of Texas, Dallas, in the Spring of 2019. The workshop will bring together researchers from different disciplines including computational and applied mathematics, statistics, computer science, and engineering to report on cutting-edge methodologies and state-of-the-art computational algorithms in data science. The workshop will provide an opportunity to all the participants to submit their related works to a special issue in the journal of Inverse Problem and Imaging (IPI). The funding provided will be primarily allocated in support of junior researchers such as graduate students, post-docs, and entry-level faculty members, specifically to under-represented minorities and women in the STEM. The organizers will coordinate invited speakers to serve as mentors to junior researchers during the poster session and the career luncheon. The organizers also invite speakers from different countries to promote international collaborations. Due to the blooming of 'big data' and an emerging field of data science, there is a need to bring together researchers from different disciplines to keep up with recent developments. The objectives of this workshop are (1) to facilitate discussions and foster collaborations among the participants with different backgrounds and expertise; (2) to attract new researchers to the field of data science and to offer mentoring service to junior participants in this field; and (3) to bridge the gap between the theoretical development in academia and practical applications in industry. The proposed workshop will be multidisciplinary with topics ranging from scientific computing and statistics to various applications in data science. As a result, this workshop will strengthen the relationship between mathematicians and other scientists/engineers who are interested in data science. In addition, the workshop will advance the development of computational methods, statistical theories, and tools for big data analysis. Furthermore, the workshop will build close connections between academia and industry to establish and facilitate research collaborations in a variety of data-driven applications.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.

2019年春季，将在得克萨斯州达拉斯分校举行有关数据科学数学/统计方法的最新发展的研讨会。该研讨会将汇集来自不同学科的研究人员，包括计算和应用数学，统计学，计算机科学和工程，以报告有关最先进方法论的最先进方法和尚未计算的algergorms alggormss Science。研讨会将为所有参与者提供一个机会，将相关作品提交给《反问题与成像杂志》（IPI）的特刊。所提供的资金将主要分配，以支持初级研究人员，例如研究生，毕业后和入门级教职员工，特别是在STEM中占代表性不足的少数民族和女性。在海报会议和职业午餐会上，组织者将协调受邀演讲者，以担任初级研究人员的导师。组织者还邀请来自不同国家 /地区的演讲者促进国际合作。 由于“大数据”和新兴的数据科学领域的开花，有必要将来自不同学科的研究人员汇集在一起​​，以跟上最近的发展。该研讨会的目标是（1）促进具有不同背景和专业知识的参与者之间的讨论和促进合作； （2）吸引新的研究人员进入数据科学领域，并向该领域的初级参与者提供指导服务； （3）弥合学术界理论发展与行业实践应用之间的差距。拟议的研讨会将是多学科的，其主题从科学计算和统计数据到数据科学的各种应用。 结果，该研讨会将加强对数据科学感兴趣的数学家与其他科学家/工程师之间的关系。此外，研讨会将推进计算方法，统计理论和大数据分析工具的开发。此外，该研讨会将在学术界与行业之间建立紧密的联系，以在各种数据驱动的应用程序中建立和促进研究合作。该奖项反映了NSF的法定任务，并被认为值得通过基金会的知识分子优点和更广泛的影响标准通过评估来进行评估。