My research lies in graph theory, particularly, spectral graph theory, which is
the interplay between graph theory and linear algebra. There are many different
types of matrices from graphs like adjacency matrices, Laplacian matrices, etc.,
which are representations of graphs. In spectral graph theory, we concern with
how linear algebra on those matrix representations like finding eigenvalues, etc.,
can be used to describe and interprete the underlying graph of that representation.
This can be a useful way of thinking about graphs since it helps to classify graphs
(according to their matrix representations) and since there are a lot of nice linear
algebra results that can be translated to graphs that may not necessarily be clear
by looking at the graph alone.
