8月10日，将在中国科学院计算技术研究所召开“首届大数据与网络科学论坛”，该论坛每年将不定期举行多次，其宗旨是交流相关领域最新的研究进展并搭建学术界、产业界与投资界在共同关注的问题上进行对话的平台。

以下是第一届论坛的信息。无需报名，完全免费！

时间：8月10日下午3:00。

地点：北京市海淀区科学院南路6号，中国科学院计算技术研究所一楼报告厅。

日程：

3:00-4:00 特邀报告（公开）

斯坦福大学，Dr. JureLeskovec，社会网络研究国际领军学者

报告题目：The Flowof Information in Social Media Networks

4:00-4:45 讨论及茶歇（公开）

4:45-5:30 嘉宾座谈（公开）

         主题：大数据的机遇和挑战

         已确认参加的嘉宾包括（字母序排列，还要多找一些，讨论可以久一点）：

         Tao Lei（雷涛），北京云基地副总裁，云基地大数据战略主要智囊

         Jure Leskovec，斯坦福大学计算机系教师，社会网络国际领军学者

         Feng Li（李丰），IDG资本合伙人，近期关注大数据方面的创新创业

         Meng Su（苏萌），北京大学光华管理学院市场营销系副主任，博士生导师，百分点科技创始人

         Xiaoru Yuan (袁晓如)，北京大学计算机学院，教授，博士生导师

         Ming Zhang（张铭），北京大学计算机学院，教授，博士生导师

         主持人（待定，没有人就我自己主持，啦拉里啦啦）

5:30-6:00 内部讨论

6:00-8:00 晚宴

组织者：程学旗（中国科学院计算技术研究所）

        沈华伟（中国科学院计算技术研究所）

        周  涛（电子科技大学互联网科学中心）

----摘要----

With an increasing amount of social interaction taking place in on-line settings, we are accumulating massive amounts of data about phenomena that were once essentially invisible to us: the collective behavior and social interactions of hundreds of millions of people. Analyzing this massive data computationally offers enormous potential both to address long-standing scientific questions, and also to harness and inform the design of future social computing applications: What are emerging ideas and trends? How is information being created, how it flows and mutates as it is passed from a node to node like an epidemic?

We discuss how computational perspective can be applied to questions involving structure of online networks and the dynamics of information flows through such networks, including analysis of massive data as well as mathematical models that seek to abstract some of the underlying phenomena.

----简历----

Jure Leskovec is assistant professor of Computer Science at Stanford University where he is a member of the Info Lab and the AI Lab. His research focuses on mining large social and information networks. Problems he investigates are motivated by large scale data, the Web and on-line media. This research has won several awards including best paper awards at KDD (2005, 2007, 2010), WSDM (2011), ICDM (2011) and ASCE J. of Water Resources Planning and Management (2009), ACM KDD dissertation award (2009), Microsoft Research Faculty Fellowship (2011), Alfred P. Sloan Fellowship (2012) and NSF Early Career Development (CAREER) Award (2011). The research has also been mentioned in popular press outlets such as the New York Times, the Wall Street Journal, the Washington Post, MIT Technology review, NBC, BBC, CBC and Wired. Jure has authored the Stanford Network Analysis Platform (SNAP, http://snap.stanford.edu), a general purpose network analysis and graph mining library that easily scales to massive networks with hundreds of millions of nodes and billions of edges. Jure serves on the editorial board of ACM Transactions of the Web and chaired ACM WWW conference Social networks track (2010, 2011). He received his bachelor's degree in computer science from University of Ljubljana, Slovenia, Ph.D. in machine learning from the Carnegie Mellon University and postdoctoral training from Cornell University. You can follow him on Twitter @jure.