International Conference on Mathematics of Data Science

数据科学是一个新兴的跨学科科学技术领域。它旨在开发理论、方法和技术，从各种结构化或非结构化形式的原始数据中提取有用的知识或见解，如信号、雷达、声音、图像、视频和文本，以做出明智的决策。数据科学使用的理论和方法来自数学、统计学、信息科学和计算机科学等广泛领域中的许多领域。数学在数据科学中扮演着不可或缺的角色。为了汇聚与数据科学相关的各个领域的活跃研究人员和行业从业者，确定数据科学中的数学和统计挑战，数据科学数学国际会议将于2018年11月3-4日在老道明大学校园举行。会议网址为：http://icmds2018.org.会议邀请的演讲者是数据科学领域的国际知名研究人员，他们将讨论该领域的关键数学问题。会议将促进不同领域的研究合作，培养学术界和产业界的研究伙伴关系，特别是鼓励青年人才在数据科学领域工作。这笔资金将仅用于支持美国大学和研究机构相关领域的初级研究人员和研究生参加会议。这支持向数据科学领域招聘年轻人才，并为迎接大数据时代的科学挑战做好下一代研究人员的准备。特别努力从非裔美国学生和女性学生等代表性不足的群体中招募研究生参加会议。会议将涵盖对数据科学至关重要的数学主题。在数据科学领域，数学提供了表示数据集的函数空间，描述数据集的相似性和差异性的近似方法，从原始数据中提取信息的优化方法，以及描述数据中各种概念之间的深刻关系及其统计分析的分析几何工具。数据科学的进一步发展要求数学发挥主导作用。例如，为什么深度学习在某些应用中非常有效，而在其他场景中效率较低，这一点还没有完全理解。这需要对深度学习中的基本问题有数学上的理解。所有这些问题都将是会议的重点。具体来说，它的范围包括大数据集的稀疏表示，适合大数据分析的函数空间，机器学习的数学基础，信号图像处理，大数据的统计分析，数据分析的凸或非凸稀疏优化，大数据的可伸缩算法和数据科学的应用。该项目的科学和社会更广泛的影响在于，会议将促进数学、统计学、计算机科学、工程和工业应用的互动，支持数据科学的跨学科领域，并将为年轻学者提供一个平台，了解和讨论该领域具有挑战性的数学问题。网站：https://sites.wp.odu.edu/icmds2018/This奖反映了美国国家科学基金会的法定使命，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。

Data science is an emerging interdisciplinary field of science and technology. It aims at developing theory, methods and techniques for extraction of useful knowledge or insights from raw data in various structured or unstructured forms such as signal, radar, sounds, images, videos and texts to make smart decisions. Data science employs theories and methods drawn from many fields within the broad areas of mathematics, statistics, information science, and computer science. Mathematics plays an indispensable role in data science. To bring together active researchers in various fields related to data science and practitioners in industry to identify mathematical and statistical challenges in data science, the International Conference on Mathematics of Data Science is being held on the campus of Old Dominion University on November 3-4, 2018. The conference website is http://icmds2018.org. The conference invited speakers are internationally known researchers in the field of data science and will address critical mathematical issues of the field. The conference will promote research collaboration among different areas, cultivate research partnership between academia and industry and, in particular, encourage young talents to work in the field of data science. The funds will solely be used to support junior researchers and graduate students in related fields at US universities and research institutions to attend the conference. This supports the recruitment of young talent to the field of data science and preparation of the next generation researchers to meet the scientific challenges in the big data era. Special efforts are made to recruit graduate students from underrepresented groups such as African American students and female students for the conference participants.The conference will cover mathematical topics crucial to data science. In the field of data science, mathematics has provided functional spaces to represent data sets, approximation approaches to characterize similarity and difference of data sets, optimization methods to extract information from raw data, and analytical, geometrical tools to describe insightful relationships among various concepts in data and their statistical analysis. Further development of data science demands that mathematics play a leading role. For example, it is not yet fully understood that why deep learning is very efficient for certain applications while less efficient in other scenarios. This requires mathematical understanding of the fundamental issues in deep learning. All these issues will be the focus of the conference. Specifically, its scope covers sparse representation of big data sets, functional spaces suitable for big data analysis, mathematical foundation of machine learning, signal image processing, statistical analysis for big data, convex or non-convex sparse optimization for data analysis, scalable algorithms for big data and applications of data science. Scientific and societal broader impacts of this project lie in the aspects that the conference will promote interaction of mathematics, statistics, computer science, engineering and industrial applications, which support the interdisciplinary field of data science, and it will provide a platform for young scholars to learn about and discuss challenging mathematical issues in the field.Website: https://sites.wp.odu.edu/icmds2018/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.