Erdun Gao

About Me

I am a Research Fellow at the RAIR, AIML, where I am a member of the KIPS Group led by Prof. Dino Sejdinovic. I received my Ph.D. in Applied Statistics (2025) from the School of Mathematics and Statistics at The University of Melbourne, where I was part of the Machine Learning and Reasoning (MLR) Group, advised by Prof. Mingming Gong and Prof. Howard Bondell. I also hold an M.S. in Signal and Information Processing (2020), supervised by Prof. Zhibin Pan, and a B.E. in Information Engineering (2017), both from the School of Information and Communication Engineering, Xi’an Jiaotong University.

Research Interests

My research focuses on building trustworthy decision-making systems for real-world environments. I am particularly interested in integrating causal reasoning and uncertainty quantification into modern AI systems, including large language models, agents, and world models. More broadly, I study the full pipeline required to realize such systems, from data selection and model design to efficient learning and reliable inference. My work is motivated by the view that prediction alone is insufficient for robust decision-making under distribution shift, partial observability, and limited data.

• Causal Foundations: Causal Discovery, Causal Effect Estimation, and Causal Experimental Design.
• Causal AI Systems: Causal LLMs, Causal Agents, and Causal World Models.
• Uncertainty & Decision-Making: Uncertainty Quantification, Information-Theoretic Acquisition, and Data-Efficient Learning.