Bayu Trisedya is a Research Fellow at the ARC Centre of Excellence for Automated Decision-Making and Society and RMIT School of Computing Technologies.

Bayu completed his doctoral research, which investigates knowledge base enrichment techniques, including knowledge graph entity alignment, entity and relationship extraction, and entity description generation, at the School of Computing and Information Systems, University of Melbourne.

Bayu has a particular research interest in natural language processing, information extraction, knowledge graph, and graph neural networks. He will contribute to the ADM+S Centre’s Machines program, focusing on designing an interpretable graph neural networks model and handling bias on knowledge graph embeddings.