Intelligent data analysis: big vs bad

时间:2018年6月21日(周四)15:00-16:30

地点:实验15楼207

报告题目:Intelligent data analysis: big vs bad

报告人:Zidong Wang 

Department of Computer Science, Brunel University, London, Uxbridge, Middlesex, UB8 3PH, U.K.

Zidong.Wang@brunel.ac.uk



报告摘要:

In this talk, we discuss another side of big data analysis, bad data analysis, where the badness means the complexities resulting in the reproducibility issues. Some background knowledge is first introduced on the volatility of the big data analysis, which shows 1) “big” does not necessarily mean “better” and 2) the so-called multi-objective data analysis (against badness) is vitally important in advancing the state-of-the-art. Two examples are used for demonstration of the big data analysis, one for big data from complex networks and the other for big data from gene expression image processing. Finally, conclusions are drawn and some future directions are pointed out.


报告人简介:

王子栋博士现任英国布鲁奈尔大学工程设计与物理科学学院终身教授。王子栋教授于1996年获得德国洪堡基金,1998年获得日本科学促进会基金,2002年获得香港大学威廉蒙基金。多年来从事控制理论(随机控制,鲁棒控制,非线性控制,模型简化)、信号处理、生物信息学方面的研究,在SCI刊物上发表国际论文四百余篇。现任或曾任十二种国际刊物的主编、副编辑或编委,包括Neurocomputing主编;国际系统科学杂志执行主编;IEEE自动控制汇刊副编缉;IEEE控制系统技术汇刊副编缉;IEEE神经网络汇刊副编缉;IEEE系统、人、与控制汇刊副编缉;IEEE信号处理汇刊副编缉等。现为IEEE Fellow,IEEE出版社编委,英国皇家统计学会理事。


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