Recent Developments on Mathematical/Statistical Approaches in Data Science

2019年春季将在达拉斯得克萨斯大学举办关于数据科学中数学/统计方法最新发展的讲习班。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、计算机科学和工程学，报告数据科学中的尖端方法和最先进的计算算法。研讨会将为所有参与者提供一个机会，将他们的相关工作提交给《反问题与成像》杂志(IPI)上的一期特刊。提供的资金将主要用于支持初级研究人员，如研究生、博士后和初级教职员工，特别是在STEM中代表性不足的少数群体和女性。组织者将协调受邀演讲者在海报会议和职业午餐会期间担任初级研究人员的导师。主办方还邀请来自不同国家的演讲者促进国际合作。由于大数据的蓬勃发展和数据科学的新兴领域，有必要将来自不同学科的研究人员聚集在一起，以跟上最新的发展。这次研讨会的目的是(1)促进不同背景和专业知识的参与者之间的讨论和合作；(2)吸引新的研究人员进入数据科学领域，并为该领域的初级参与者提供指导服务；以及(3)弥合学术界的理论发展和工业实际应用之间的差距。拟议的讲习班将是多学科的，主题从科学计算和统计到数据科学的各种应用。因此，这次研讨会将加强数学家和其他对数据科学感兴趣的科学家/工程师之间的联系。此外，研讨会还将促进大数据分析的计算方法、统计理论和工具的发展。此外，研讨会将在学术界和产业界之间建立密切的联系，以建立和促进在各种数据驱动的应用程序中的研究合作。这一奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

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.