Summer School on Spectral Graph Theory

A graph is a collection of vertices connected by edges. Graph theory is the study of graphs, while spectral graph theory examines the matrices associated with them. The adjacency matrix and Laplacian matrix of graphs are typically studied in spectral graph theory. The central question of spectral graph theory is to determine the properties that become prominent when the graph is represented as a matrix.

The eigenvalues and eigenvectors of the matrices associated with a graph are extensively studied in spectral graph theory. These linear-algebraic quantities convey powerful information about the graph. Thus, spectral graph theory enables a thorough exploration of the structure and dynamics of a graph, particularly in the case of large graphs and big data scenarios.

Spectral graph theory has a wide range of real-world applications in various fields, including chemistry, biology, computer science, electrical engineering, civil engineering, naval engineering, mining engineering, urban planning, economics, finance, and social science. It is commonly used in the design of efficient algorithms for various sub-specialties of computer science and engineering. Therefore, it is an intriguing topic for exploration. 

Contact:

Dr. Md. Saidur Rahman
Professor, Department of Computer Science and Engineering
Bangladesh University of Engineering and Technology (BUET)
ECE Building, BUET
West Palashi Dhaka-1205, Bangladesh
Email: saidurrahman@cse.buet.ac.bd
https://saidurrahman.buet.ac.bd/