Ignavier Ng

I am a PhD student in the Causal Learning and Reasoning Group at Carnegie Mellon University, advised by Profs. Kun Zhang and Peter Spirtes.

My research interests lie in machine learning and causal inference. Most recently, I have been working on causal representation learning, aiming to uncover latent structures and representations from data, and investigating how it enables more generalizable and trustworthy machine learning.

I have also worked on various aspects of causal structure learning (a.k.a. causal discovery), including continuous optimization, latent confounders, feedback cycles, and selection bias, with the goal of improving its applicability and scalability.

Previously, I obtained my master's degree from University of Toronto and bachelor's degree from Hong Kong University of Science and Technology. During my study, I have spent time at Amazon, Microsoft Research, Google X, Mila, and MIT CSAIL.