My research is focused on developing machine learning methods capable of handling diverse and heterogeneous data sources. In particular, I utilize and develop techniques in optimal transport, Bayesian nonparametric models, domain adaptation/generalization, and large model pretraining & fine-tuning. The ultimate goal of my work is to enable generalizable and reliable machine learning applications in critical sectors, such as healthcare and robotics.