学 术 报 告
报告题目： Using networks to combine ``Big Data'' and differential equation models to improve Influenza
报告人：Prof. Haiyan Wang (School of Mathematical & Natural Sciences, Arizona State University)
校内联系人：代国伟， 电话：84708351-8135
报告时间：2015年8月5日（周三）14：30－15：30
报告地点：创新园大厦A1101
报告摘要：The rich and big data generated by millions of users on social media reveals what is happening in the real world in a rapid and accurate fashion. In recent years many researchers have explored real-time streaming data from Twitter for a broad range of applications such as predicting flu trends. In this talk, we present our design and implementation of a prototype system to collect flu related twitter data. Further we use ordinary and partial differential equation models to describe the diffusion of flu related information in Twitter in both spatial and temporal dimensions. We correlate the results with official statistics from Center for Disease Control and Prevention (CDC). These results demonstrate that the system can be used to real-timely monitor spread of flu trends.
报告人简介：Haiyan Wang，1997年在美国Michigan State University获得博士学位。1997-2004年在Informative Graphics Corporation担任软件工程师。现为美国 Arizona State University 大学教授。是Mathematical Biosciences and Engineering、Advances in Differential Equations and Control Processes、Biostatistics, Bioinformatics and Biomathematics、ISRN Mathematical Analysis、Journal of Operators等杂志的编委。
Haiyan Wang教授主要从事常微分方程正解的存在性和偏微分方程在社交网络信息传播中的应用研究。在国际权威杂志 J. Nonlinear Sci., J. Differential Equations, Discrete Contin. Dyn. Syst.等上发表学术论文50余篇。在Springer出版专著1部。特别在常微分方程正解的存在性方 面做了大量开创性的工作。也研究了反应扩散方程的 行波解。他首次用偏微分方程理论研究在线社交网络的信息传播过程，建立了若干重要模型和实证方法， 揭示了大量有趣的信息传播现象。所获得的结果对于理解许多生物和信息、传播现象提供了重要的新的观念。他所发表的论文被同行引用达3000余次。
数学科学学院
2015年8月3日
