Welcome to Graph Research Lab

We are a research team at the School of Computing, Australian National University. Our overarching research goal is to explore and understand graph-structured data. In today’s real-world applications, graphs are ubiquitously used for representing complex objects and their relationships such as cities in a road network, atoms in a molecule, friendships in social networks, connections in computer networks, and links among web pages. We focus on the following research areas:

  • Graph theory and algorithms
  • Machine learning on graphs
  • Bridging between graph theory and machine learning
Check out our recent research highlights and research opportunities.


16 May 2023

Our latest work on batch-dynamic algorithms, "BatchHL+: Batch Dynamic Labelling for Distance Queries on Large-Scale Networks", is accepted for publication in The VLDB Journal. Congratulations!

8 May 2023

Gathika's work "Contrastive Learning for Supervised Graph Matching" is accepted to UAI 2023. Well done, Gathika!

25 Apr 2023

Sean's paper "Local Vertex Colouring Graph Neural Networks" is accepted to ICML 2023. Congratulations, Sean!

26 Mar 2023

Ghodai's paper "Learning Data Teaching Strategies via Knowledge Tracing" is to appear at Knowledge-based Systems. Good work, Ghodai!

25 Mar 2023

Congratulations to Ghodai for submitting your thesis. Well done!

9 Mar 2023

Congratulations on your doctorate, Asiri. Well deserved!

24 Feb 2023

A "PhD Opportunity" is available in Graph Algorithms.

29 Jan 2023

Farhan's work "Efficient Maintenance of Highway Cover Labelling for Distance Queries on Large Dynamic Graphs" is accepted for publication in World Wide Web. Congratulations Farhan!

23 Jan 2023

Our paper "N-WL: A New Hierarchy of Expressivity for Graph Neural Networks" is to appear at ICLR 2023.

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