My current work concerns graph theory and its applications, the design, analysis, implementation and performance evaluation of algorithms, and data-intensive computing.
Graph theory and its applications: Graphs model many important applications and are also tools to solve many other theoretical problems. We often start with probing fundamental theoretical problems such as the structures of graphs with certain properties. With these properties, we then usually design efficient algorithms and solve applications. One example we are working on is the graph connectivity augmentation problem with partition constraints. In this problem, a minimum set of edges are required to add to a graph such that the connectivity of the resulting graph increases. Furthermore, the added set of edges must follow given constraints. This problem has applications on many problems, such as the design of reliable networks, the security of statistical tables and the drawing of planar graphs.
Design, analysis, implementation and performance evaluation of algorithms: Algorithms is one of the cores of computer sciences. We are interested in all aspects of researches in algorithms which include finding new algorithms for interesting problems and designing efficient implementations to solve real-world applications. We are interested in both sequential, parallel and distributed algorithms.
Data-intensive computing: With the rapid development of computer and communication technology, it has become much easier to access or store massive amounts of data electronically. We are interested in the research problems concerning efficient usage of massive data which include data privacy, issues in large scale social networks and computer Chinese chess. In data privacy, there seems to be a problem in mining massive on-line data for the public goods for fear of privacy leakage. In view of this, we are developing formal models and practical systems for privacy protection, pricing mechanisms for privacy leakage and secure multi-party computation. We also wish to find efficient algorithms for checking and preventing privacy leakage. In large scale social network, we wish to study various issues which include efficient simulation and dynamic processing of social networks. In computer Chinese chess, we study memory-efficient algorithms for constructing huge endgame database, efficient algorithms for using these databases in computer Chinese chess programs, and computer models to check Chinese chess tie-breaking rules. It is worth while noting that our researches in massive data often benefits from results obtained from our studies in graph theory and algorithm.