数据分析算法的融合与人才培养

Mathematics has been the foundation of natural sciences, and provides them with tools and methods which enable precise quantification and descriptions of natural phenomenon. The interaction between mathematics and natural sciences motivates the development of mathematics itself. The 21st century is the century of data. The creation, distribution, integration, interpretation and manipulation of data have become an important part of our society. Advances in computer technology, internet, hardware design have stimulated a rapid increase in the amount of data collected from various fields in science, engineering and social media. It brings new opportunities to mathematics, as well as new challenges. This project focuses on two aspects: research and education. For research, we will study the possibility of merging algorithms for data analysis that come from areas in computational mathematics, statistics, computer science and optimization. We shall study connections and differences among these algorithms, and design new algorithms for specific data analysis tasks by combining the merits of existing algorithms. For education, we will organize summer schools and short-term courses to teach students and junior researchers on data analysis algorithms in an integrated fashion.

长久以来，数学是一切自然科学的基础，它为其它科学的定量、精确描述提供了语言、工具和方法，而数学与自然科学的相互作用也一直是数学的活力来源之一。进入21世纪后，我们步入了大数据的时代，数据的生成、传播、整合、分析和处理已经成为了我们生活中不可或缺的一部分。随着计算机技术、互联网、仪器硬件设计的飞速发展，在自然科学、高新技术行业、社交媒体等领域中产生的数据呈爆炸式增长，这为数学带了的新的挑战，同时也带来了新的契机。本课题的主要目的分为科研和人才培养两方面。在科研方面，我们将研究来源于计算数学、统计、计算机、优化的数据分析算法之间的区别与联系，并针对具体问题融合各类算法的优点提出新的数据分析算法；在人才培养方面，我们将开设暑期班和短期课程，也让学生和年轻学者对数据分析算法有系统的了解，从而能更好的解决其科研中的数据分析问题。