Dr. Wei Wang

wei's picture

Associate Professor
School of Computer Science and Software Engineering
Xi'an Jiaotong Liverpool University
Dushu Lake Higher Education Town
Suzhou, 215123

Phone: +86 (0) 512 88167736
E-mail: wei.wang03[AT]xjtlu.edu.cn
WWW: page at XJTLU

Research Interests

My research interests lie in the broad area of Data and Knowledge Engineering.


Journal Articles
Book Chapters
Conference Papers

PhD Projects


Distributed Intelligence for Big Smart City Data Processing
The project applies techniques developed in the areas of semantic Web, machine learning and data mining to extract knowledge from the large-scale collaboratively generated data on the social Web, and attempts to move one step further towards harvesting the "collective intelligence", in particular, in the domain of scientific research. It aims to develop new learning methods and algorithms to differentiate and unveil the true semantics of tags as well as the relations among them, and to abstract them in formal taxonomical or ontological knowledge. More importantly, the research aims to elicit evolving semantics from the social dynamics and to implement efficient learning mechanisms to address the computational challenges. The significance of the research is to enable better understanding of the social interactions for human by deriving evolving knowledge from collectively generated contents and to improve content discovery, search, ranking and attention support in general.

Learning and Evolving Knowledge from User Generated Social Media Data
The project aims to design and develop methods and apparatus for processing and analysing city data, based on the key concept of "distributed intelligence". In particular, the novelties include: (1) distributed intelligence for processing big smart city data, (2) information abstraction and representation for city data of different nature, (3) deep knowledge discovery for developing truly smart city applications, and (4) trust modelling for assessing the trustworthiness of discovered knowledge.

Data-driven Cyber-Physical-Social System for Knowledge Discovery in Smart Cities (with University of Surrey, completed in Oct 2018)
The project aims to design a data-centric framework for CPSS that contains management and processing capabilities for knowledge discovery from mobile sensing data and social networks content. The contributions include a data retrieval method that addresses the issue of searching for both current and historical sensor measurement values from heterogeneous sources in mobile sensing environments. A novel spatio-temporal model for regression analysis that can perform missing data estimation in incomplete datasets obtained from mobile sensing sources has been developed that outperforms the state-of-the-art noticeably. Finally, the designed knowledge discovery mechanism merges and correlates physical and social sensing data, enabling links between different scales/types of data: numeric values of sensor observation data and textual content of social networks messages.


Journal Reviewer
Special Issues

Invited Talks and Tutorials