About Me

I am a Research Fellow at the University of Technology Sydney and a Visiting Scientist at CSIRO. I develop novel techniques for machine learning and artificial intelligence, with an emphasis on approaches that are statistically principled, computationally scalable, and operationally trustworthy.

My current research focuses on causality, motivated by the view that causal reasoning is a foundational primitive of intelligence. That focus has emerged from several years spent exploring three closely connected areas:

• Causal discovery
  Uncovering the underlying mechanisms that generate observed data, separating true cause-and-effect relationships from spurious associations to enable deeper scientific understanding.
• High-dimensional learning
  Extracting reliable structure and signal from datasets with thousands or millions of measured variables, where classical statistical principles break down and new techniques are needed.
• Bayesian inference
  Using probabilistic reasoning to integrate prior knowledge with new evidence, yielding transparent measures of uncertainty that guide reliable decision-making.

Before my current role, I was a Research Associate at the University of New South Wales, having completed my PhD at Monash University. Earlier in my career, I worked at KPMG, where I advised financial institutions on quantitative risk management. I began my academic journey at the University of Sydney, where I completed my undergraduate studies.

You can find a list of papers and talks in my curriculum vitae.