My current research in machine learning focuses on large language models, (inverse) reinforcement learning, imitation learning, trustworthy learning, and algorithmic fairness. In the past, I have worked on representation learning, kernel methods, and optimization.

I work on applications in longitudinal cancer treatment, pattern recognition, document analysis, image processing, and any prediction problem that is useful in life.