Causal Data Science Lab @UIUC

I am Yonghan Jung, an assistant professor in the School of Information Sciences at the UIUC and the leader of the Causal Data Science Lab. I am also a faculty affiliate at the National Center for Supercomputing Applications (NCSA), and Illinois Informatics.

My research advances causal inference methodology through three core areas that address the challenges of real-world data complexity, computational scalability, and actionable decision support:

1. Pragmatic Causal Inference: Advancing causal inference methods that address real-world challenges such as unmeasured confounding, limited overlap, and complex data-generating processes.

2. Scalable Causal Inference: Designing computationally efficient and statistically robust methods that scale to high-dimensional and large-scale datasets.

3. Causal Decision Making: Creating algorithms that leverage causal reasoning to support robust and safe decision making in complex, high-stakes environments.