Recently in academic Category

The academic communities that interest me are those related to image processing, machine intelligence, information systems, etc. I hope I will be able to contribute to those communities in the future: ACM, IEEE Signal Processing Society and IEEE Computer Society.

1. ACM

   ACM, the world's largest educational and scientific computing society, delivers resources that advance computing as a science and a profession. ACM provides the computing field's premier Digital Library and serves its members and the computing profession with leading-edge publications, conferences, and career resources.

2. IEEE Computer Society

   With nearly 85,000 members, the IEEE Computer Society is the world's leading organization of computing professionals. Founded in 1946, and the largest of the 39 societies of the Institute of Electrical and Electronics Engineers (IEEE), the CS is dedicated to advancing the theory and application of computer and information-processing technology.

   The CS serves the information and career-development needs of today's computing researchers and practitioners with technical journals, magazines, conferences, books, conference publications, and online courses. Known worldwide for its computer-standards activities, the CS promotes an active exchange of ideas and technological innovation among its members.

3. IEEE Signal Processing Society

The IEEE Signal Processing Society is an international organization whose purpose is to: advance and disseminate state-of-the-art scientific information and resources; educate the signal processing community; and provide a venue for people to interact and exchange ideas. They have some publications like IEEE Transaction on Multimedia, IEEE Transaction on Image Processing, and IEEE Multimedia Magazine which publish very good quality papers in areas of multi media types.

Frankly speaking, it is after I came to IST when I first heard about the term "I-school", and my understanding of this term at the beginning is places where researchers from different areas work together, and where education is of a multi-disciplinary nature. I-schools have various origins, such as information science, library science, computer science, HCI, economics, management, policy, sociology, etc., but all have the same focus: information. The cross-disciplinary, inter-disciplinary nature is probably the most distinguishing feature of I-schools compared to other traditional disciplines.

As being a computer science student for six years, I found myself quite interested in research areas where different aspects of technology and people are combined. It is not easy to say which side is more important, but lots of people begin to believe that studies based on a more comprehensive view is probable to achieve valuable and even unexpected results.

It is obvious that today's technology is highly relied on the understanding of people's role in different domains of the society. Traditional disciplines of information like library science, computer science, etc. are increasingly intersected with disciplines on the social side. The recognition that study of these areas separately cannot provide solutions to the complicated problems existing in today's social environment encourages more effort devoted to this newly emerging area. Instead of focusing on the technical aspects of information generation, storage, distribution, retrieval, etc., I-school also concerns the people side of these activities. Though information flow is extremely variable, understanding of certain patterns in different domains can facilitate information usage in those areas, which in turn can have great impact on people and technology in that society.

Imagine ISchools: information, initiate, intellect, impact, innovate, introspect, idealize, insight, imagine?

Education

Research Interests

• Semantic sensitive image retrieval
• High-level image analysis and understanding
• Image annotation
• Shape analysis

Publication

1. Lei Yao, Jian Liu, Jiangqin Wu, "An Approach to the Compression of Residual Data with GPCA in Video Coding," Proceedings of the Pacific-Rim Conference on Multimedia, pp 252-261, China, 2006.
2. Jian Liu, Yueting Zhuang, Lei Yao, Fei Wu, "A Novel Scalable Texture Video Coding Scheme with GPCA," Proceedings of the International Conference on Acoustics, Speech, and Signal Processing, pp I-993 - I-996, Honolulu, 2007.
3. Jian Liu, Fei Wu, Lei Yao and Yueting Zhuang, "A Prediction Error Compression Method with Tensor-PCA in Video Coding," Proceedings of the International Workshop on Multimedia Content Analysis and Mining, pp 493-500, China, Springer Berlin, 2007.