Lijuan Li
Papers
2
Total Citations
5
H-Index
2
About
Lijuan Li’s research bridges artificial intelligence and biomedical engineering, with key contributions in multi-agent decision-making and human–machine interaction. Her most cited work, “Controlling Large Language Model-based Agents for Large-Scale Decision-Making: An Actor-Critic Approach” (2023), tackles the critical challenge of scaling LLM-powered agents in multi-agent systems. By proposing a novel actor-critic framework, Li addresses the dual problems of LLM hallucination and coordination breakdown as agent populations grow—a pressing issue for autonomous systems in logistics, robotics, and smart infrastructure. This work has already garnered 3 citations, signaling its timely relevance. In parallel, her earlier study on hand gesture recognition using surface electromyography (sEMG) (2021) advances rehabilitation robotics by applying moving average filtering to improve feature extraction, achieving higher recognition accuracy for prosthetic control. With 2 citations, this work underscores her commitment to translating AI into tangible assistive technologies. Li’s research uniquely spans theoretical frameworks for LLM-based agents and practical signal-processing innovations, demonstrating versatility and impact. Her work is essential reading for researchers exploring scalable AI coordination and bio-signal-driven human–machine interfaces.
Research Focus
Key Achievements
Top Papers
- 1
- 2