Erdun Gao

About Me

I am a Research Fellow at the Responsible AI Research Centre, Australian Institute for Machine Learning, 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 causality and causal machine learning, with foundations in causal discovery, causal effect estimation, and causal experimental design. Building on these foundations, I am increasingly interested in the intersection of causal learning and generative/agentic AI, particularly how intelligent systems can acquire information, design experiments, evaluate interventions, and make decisions efficiently. More broadly, I explore connections with foundation models, uncertainty quantification, and data-efficient learning.

• Causal Foundations: Causal Discovery, Causal Effect Estimation, and Causal Experimental Design.
• Causal Learning & Experimentation: Adaptive and Generative Experimental Design, Causal Decision-Making, and Causal Foundation Models.
• Causal AI & Agentic Systems: Agentic Experimentation, Causal Evaluation of AI Systems, and Causal World Models.
• Other ML: Uncertainty Quantification, Data Selection, and Data-Efficient Learning.