Abstract:

We live in an era of big data, where everyone can access a steam of data as scientific treasures at their fingertips. Traditional statistics has been instrumental for manipulating experimental data that are collected under a priori assumptions at a limited dimension, but it can hardly meet the need of big data analysis. Big data often emerge as dynamic graphs or networks in which nodes are linked in a nonlinear, stochastic manner, with the directionality, sign and weight of links determining the networks as a cohesive whole. In this talk, I will be presenting a new norm of statistical thinking, which combines evolutionary game theory, ecological niche theory and graph theory through quasi-dynamic modeling, to create a graph representation theory of statistics. This theory could leverage statistics to better predict the future and transform big data into practical values.

Biography:

邬荣领现任北京雁栖湖应用数学研究院副院长、研究员、复杂系统拓扑统计学理论与应用北京市重点实验室主任、清华大学丘成桐数学研究中心曾思明讲座教授。曾任美国宾夕法尼亚州立大学统计学杰出教授、公共卫生科学杰出教授、统计遗传研究中心主任。获得国家杰出青年基金项目（B类）、教育部长江讲座教授、中组部国家特聘专家、北京市科技战略人才，入选美国科学促进会会士、美国统计学会会士，获佛罗里达大学研究基金教授奖、宾夕法尼亚州立大学杰出大学教授奖、Floyd科学创新等。
开创性地将数学模型引入生物性状基因定位框架，提出了功能作图理论，这一理论已成为现代统计基因组学中的重要研究工具之一。近年来，面对大数据时代传统统计学和技术方法的挑战，他将功能作图与进化博弈论、图论相结合，开创了功能图论新范式，逐渐成为系统生物学、空间生物学、系统药理学、网络医学及复杂系统研究等领域的重要分析工具。