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  题目:大数据时代的情景感知计算 Context-aware Computing in the Era of Big Data
  
  报告人: 张大庆,教授,中国千人计划国家特聘专家,北京大学讲座教授
  
  时间: 2015年12月25日星期五上午10:00am
  
  地点: 电信大楼309室
  
  邀请人: 赵生捷
  
  报告人简介:张大庆,北京大学讲座教授, 国家千人计划入选者。1996年获得意大利罗马大学博士学位。曾任法国巴黎国立电信学院(Institute TELECOM)一级终身教授,法国科学院(CNRS)教授, 新加坡资讯通讯研究院(I2R) 智能家庭实验室创建主任,情景感知系统部创建主任。主要研究方向包括普适计算、情景感知计算、移动计算及感知大数据分析等。在相关国际期刊、会议发表学术论文200余篇,论著5本。所创的情景感知模型被国际普适计算, 移动计算, 和服务计算学术界广泛采用,单篇最高它引次数达1000余次 (根据Google Scholar), 并被普适计算领域顶级会议IEEE PerCom 2013授予十年最具影响力论文 (Ten Years CoMoRea Impact Paper Award)。近年来在群智感知、无线感知、感知大数据分析等领域工作, 先后获得国际会议 ACM UbiComp2015, IEEE UIC 2015和2012, IEEE CPSCom 2013, Mobiquitous 2011 最佳论文奖或提名奖。现为ACM Transactions on Intelligent Systems and Technology, IEEE Transactions on Big Data等4个国际期刊的编委, 担任过10多个国际会议的大会或程序委员会主席, 及普适计算顶级会议Ubicomp, PerCom程序委员会委员,应邀在10多个国际会议做大会特邀报告。
  
  内容提要: Since the seminal work of Schilit and Theimer on context-awareness in 1994, great research progress has been made in context-aware computing field. Due to limited deployment scale of sensors and devices, in early years context-aware computing focused mainly on understanding and exploiting personal context in single smart spaces. As a result of the recent explosion of sensor-equipped mobile phones, the phenomenal growth of Internet and social network services, the broader use of the Global Positioning System (GPS) in all types of transportation, and the extensive deployment of sensor network and WiFi in both indoor and outdoor environments, the digital footprints left by people while interacting with cyber-physical spaces are accumulating with an unprecedented speed and scale, resulting in “Big Data”. The technology trend towards crowd sensing is creating new challenges and opportunities for context-aware computing – with huge amount, large scale, multi-modal, different granularity, diverse quality of data from various data sources. In this talk, I will start by examining the status quo of context-aware computing research in 2004 and then present the research direction called "social and community intelligence (SCI)” as a natural extension of context-aware computing in the era of big data, with emphasis on extracting community and society level context. In particular I will introduce our recent work in crowd-sensed data analytics, including mining large scale taxi GPS data, mobile phone data and social media data for enabling innovative applications in smart cities.
  
  欢迎各位老师同学踊跃参加!
 

发布日期:2015-12-23

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