I am a professor in the philosophy department and an affiliate faculty member in the machine learning department at Carnegie Mellon University, and a visiting professor of machine learning at MBZUAI. My research interests lie in machine learning and artificial intelligence, especially in causal discovery, causal representation learning, and explainable, trustworthy, and controllable AI from a causal perspective. A core aim of my research is to make hidden causal entities and causal processes transparent, for the purpose of intervention design, automated scientific discovery, optimal decision making, etc.

I develop methods for automated causal discovery and causal representation learning from various kinds of data, investigate learning problems including transfer learning, concept learning, and generative AI from a causal view, and study philosophical foundations of causation and various machine learning tasks. On the application side, I am interested in neuroscience, computer vision, computational finance, and climate analysis.

I work in the Causal Learning and Reasoning (CLeaR) research group, together with Clark Glymour, Peter Spirtes, Joseph Ramsey, and our students, postdocs, and visitors. I also work in the causality group and the Center for Integrative AI (CIAI) at MBZUAI. I am lucky to have the opportunity to work with all of them.

See the Research page for a summary of some of our recent work on causal discovery and machine learning (especially transfer learning).