Ruisi’s research primarily focuses on large language model (LLM) efficiency, reasoning, and AI security, specifically efficient training and inference for large foundation models while enhancing decision-making capabilities. She has been working on optimizing model architectures for faster and more resource-efficient deployment, ensuring flexible and reliable inference, and developing techniques that foster advanced reasoning.