The 2023 Gibbons Lectures series is intended to describe ongoing research in Computer Science to a wider public, organized by Faculty of Science, University of Auckland.

Jiamou Liu, School of Computer Science, University of Auckland

Thursday 25 May, 6:30pm

Venue: Lib B15 Lecture Theatre General Library Basement, (109-B15) The University of Auckland 5 Alfred Street, Auckland CBD, register your place here.

This lecture will be available to livestream here.

Graph analysis is an increasingly important tool in modern data science, providing powerful ways to represent and analyse complex structured data. In this talk, we will discuss recent advances in graph analysis, including data mining and social network analysis, as well as the use of Graph Neural Networks (GNNs) for tasks such as node classification and link prediction. We will also explore recent techniques in contrastive learning for graphs and data augmentation for graphs, which have enabled significant improvements in the accuracy and robustness of graph-based models.

Jiamou currently holds a position as a Senior Lecturer at the School of Computer Science at The University of Auckland. Graduated with a PhD in Computer Science from the same university in 2010, he has held academic positions at institutions including the University of Leipzig in Germany and AUT in NZ. Jiamou’s research is focused on a variety of areas, including data mining, multi-agent systems, and natural language processing. His work published in prestigious venues such as NeurIPS, ICML, and ACL. He has served as a Program Committee member for leading conferences in the field, including AAAI, IJCAI, and AAMAS.