Danny Wang

School of EECS, The University of Queensland, Australia

I am a PhD student at The University of Queensland (UQ), Australia, specialising in robust and trustworthy graph machine learning. My research is conducted under the supervision of Dr. Ruihong Qiu, A/Prof. Guangdong Bai, and Prof. Zi (Helen) Huang. I completed my dual Bachelor of Computer Science and Master of Data Science degrees at UQ, graduating as the class of 2023 Valedictorian.

Publications

TextTopo

Text Meets Topology: Rethinking Out-of-distribution Detection in Text-Rich Networks

EMNLP 2025 - Main Track

We introduce TextTopoOOD, a framework for modeling diverse OOD scenarios on text-rich networks, and propose TNT-OOD, a novel detection method that captures the intricate interplay between text and topology.

Paper Code
GOLD

GOLD: Graph Out-of-Distribution Detection via Implicit Adversarial Latent Generation

ICLR 2025 - Spotlight

We propose the GOLD framework for graph OOD detection, an implicit adversarial learning pipeline with synthetic OOD exposure without pre-trained models.

Paper Code
GetFair

Hate Speech Detection with Generalizable Target-Aware Fairness

Tong Chen, Danny Wang, Xurong Liang, Marten Risius, Gianluca Demartini, Hongzhi Yin

KDD 2024

We propose the GetFair framework, a novel approach for equitably detecting hate speech across diverse targets, including those unseen during training. This framework ensures fair detection with consideration of the social groups targeted in the content.

Paper Code

Teaching · Education · Awards

Teaching

  • 2024-2025: Tutor - Master of Data Science Capstone (DATA7901/7903)
  • 2024-2025: Tutor - Undergraduate and Postgraduate Course "Advanced Techniques for High Dimensional Data" (INFS4205/7205)
  • 2022: Tutor - Postgraduate Course "Introduction to Data Science" (DATA7001)

Education

  • 2024–2027: Doctor of Philosophy (PhD) in CS, The University of Queensland
  • 2020–2023: Bachelor of Computer Science/ Master of Data Science, The University of Queensland - GPA Rank 1st

Awards

  • 2023: I was selected as the class of 2023 Valedictorian for the graduation ceremony of the Faculty of Engineering, Architecture and Information Technology
  • 2020-2023: Dean's Commendation for Academic Excellence. The Faculty of Engineering, Architecture and Information Technology, has determined that students who demonstrate excellence in academic performance should receive acknowledgement of the achievement.