Research Topics

Focusing on Graph Neural Networks, Graph Federated Learning, Graph Unlearning, Directed Graph Learning, Graph Foundation Models, Graph Data Agents, Graph4LLM, LLM4Graph, Multimodal Attribute Graphs, AI4Science, etc.

Focusing on Cohesive Subgraph Mining, Community Detection and Search, Clique Enumeration and Counting, Hereditary Cohesive Subgraph Enumeration and Counting, Densest Subgraph Mining, Graph Density Decomposition, Shortest Path Queries, Group Steiner Tree Queries, Spanning Tree Maintenance, Connectivity Maintenance, Graph Centrality Computation, Graph-based Index for Vector Retrieval, etc.

Focusing on PageRank, Resistance Distance, Biharmonic Distance, Kemeny Constant, Laplacian Solver, Expander Decomposition, Spanning Tree Sampling, Random Walk Sampling, Spectral Graph Theory and Applications, etc.

Focusing on Persistent Homology, Filtration, Graph Collapse, Topology-preserving Graph Coarsening, the deep integration of Topological Data Analysis methods and Graph Mining algorithms, and their applications in graph data mining.