Research Interests

My research interests lie at the intersection of machine learning theory and optimization. I am dedicated to building a rigorous theoretical understanding of modern optimization algorithms in deep learning, analyzing their convergence, implicit bias, and generalization. At the same time, I am interested in applying these theoretical insights to the design and analysis of large language models (LLMs/MLLMs), including LLM-based approaches for modeling complex sequential and event-based data.