Keynote Speakers are listed alphabetically according to their surnames.

Professor Shi-Kuo Chang, Dept. of Computer Science, University of Pittsburgh, USA

• Title: Slow Intelligence Systems
• Abstract: 
      In this talk I will introduce the concept of slow intelligence.Not all intelligent systems have fast intelligence. There are a surprisingly large number of intelligent systems, quasi-intelligent systems and semi-intelligent systems that have slow intelligence. Such slow intelligence systems are often neglected in mainstream research on intelligent systems, but they are really worthy of our attention and emulation. I will discuss the general characteristics of slow intelligence systems and then concentrate on evolutionary query processing for distributed multimedia systems as an example of artificial slow intelligence systems......More. 

Dr Shipeng Li, Microsoft Research Asia

• Title: Media 2.0 – the New Media Revolution?
• Abstract: With the rapid development of Web 2.0 and cloud computing concept and applications, there are many unprecedented web-based multimedia applications are emerging today and they pose many new challenges in multimedia research. In this talk, I first summarize the common features of the new wave of multimedia applications which I call Media 2.0. I use 5 D’s to describe Media 2.0 principles, namely, Democratized media life cycle; Data-driven media value chain; Decoupled media system; Decomposed media contents; and Decentralized media business model. Then I explain what the implications of Media 2.0 to multimedia research are and how we should choose our research topics that could make big impacts. Finally, I use example research projects ranging from media codecs, media systems, media search and media related advertisement from MSRA to demonstrate the ideas I have talked about. I hope these ideas and principles could inspire the audience to come up with new media 2.0 research topics and applications in the future.     More.

Professor Hartmut Neven, Google 

• Title: Designing a Comprehensive Visual Recognition System
• Abstract:
      Computer vision has made significant advances during the last decade. Many capabilities such as the detection of faces or the recognition of rigid textured objects such as landmarks are now working to very satisfying levels......More.