南开大学邹长亮教授“多个数据流在线监测”监测高维数据流已经成为实时检测的异常活动日益重要，在许多数据丰富的应用程序。在这次演讲中，我会给近期的工作了简短的讨论从以下几个方面：i)制定一个有效的全球监测过程的时候，我们不知道哪个数据流的子集受到正在发生的事件; ⅱ)提供一个过程，它是能够控制条件假发现率在当我们的焦点检测变化每个单独的数据流中的每个时间点;三)提出的意义上的自由分布检测方案，它在控制运行长度分布是免费的基本分布。以下是原文。

　　On-Line Monitoring of Multiple Data Streams

　　Monitoring high-dimensional data streams has become increasingly important for real-time detection of abnormal activities in many data-rich applications. In this talk, I will give a brief discussion on recent work from the following aspects: i) develop an efficient global monitoring procedure when we do not know which subset of data streams is affected by an occurring event; ii) suggest a procedure which is able to control the conditional false discovery rate at each time point when our focus is detecting changes in each individual data stream; iii) propose a distribution-free detection scheme in the sense that its in-control run-length distribution is free of the underlying distribution.