Abstract

Given a graph and a function on its vertices, how do we partition the vertices into clusters so that (1) vertices with similar function values are in the same cluster and (2) the induced subgraph on each cluster is connected as much as possible? Such a problem has applications in detecting the sources of air pollution, image segmentation, and so on. We will go through the theoretical background of this algorithm and demonstrate some of its applications.

Bio.

Jephian C.-H. Lin is an associate professor of applied mathematics at National Yang Ming Chiao Tung University. He received his Ph.D. in mathematics from Iowa State University and completed a postdoctoral fellowship at the University of Victoria. He is actively involved in the International Linear Algebra Society (ILAS), serving the community through conference organization and related activities. His research interests include graph theory and matrix theory, particularly spectral graph theory, inverse eigenvalue problems of graphs, and the minimum rank problem, with connections to combinatorics and network analysis.

All faculty and students are welcome to join.