Key research themes
1. How can graph automorphisms be leveraged to improve graph compression methods?
This theme explores the role of graph automorphisms—symmetries within graphs—in identifying redundant structural information that can be exploited for lossless data compression. Detecting global and local graph symmetries enables the representation of graphs more succinctly by encoding automorphisms rather than enumerating all edges explicitly. The significance lies in optimizing storage and querying efficiencies for large-scale structured data where the automorphism-induced redundancies are present.
2. What algebraic and combinatorial structures underpin graph automorphisms and their extensions in homomorphisms and isomorphism problems?
This theme investigates the algebraic frameworks and complexity classifications related to graph automorphisms, graph homomorphisms (including correspondence and list homomorphisms), and two-fold automorphisms. These studies elucidate how automorphisms interrelate with homomorphism extensions, constrain isomorphism detection, and drive dichotomy results in computational complexity, thereby advancing theoretical understanding of graph symmetry operations and their algorithmic implications.
3. How do algebraic structures emerge from graph automorphisms in the context of graph associahedra and related polytopes?
This theme focuses on the algebraic and operadic structures arising from graph automorphisms manifest in convex polytopes associated with graphs, specifically graph associahedra. Through the definition of tubings and substitution operations reflecting automorphism-induced decompositions, researchers establish connections to operads, Hopf algebras, and pre-Lie coalgebras. This bridges topological and algebraic graph theories, elucidating how automorphisms govern combinatorial polytope properties and induce rich algebraic frameworks.