Biwei Huang’s research interests are mainly in three aspects: (1) automated causal discovery in complex environments with theoretical guarantees, (2) advancing machine learning from the causal perspective, and (3) using or adapting causal discovery approaches to solve scientific problems. She successfully led a NeurIPS’20 workshop on causal discovery and causality-inspired machine learning and co-organized the first Conference on Causal Learning and Reasoning (CLeaR 2022). She was named a Rising Star of the Trustworthy ML Initiative and is a recipient of the Presidential Fellowship at CMU in 2017 and the Apple Scholars in AI/ML Ph.D. fellowship in 2021.