Research Index

A novel framework combining LLM-based multi-agent systems with predictive battery thermal management for coordinating urban EV fleets. The system leverages natural language interaction for fleet operators while optimizing battery longevity and energy efficiency through distributed intelligence and real-time thermal management.

A novel framework integrating large language models with microgrid control systems for intelligent predictive maintenance and resource optimization. The system combines natural language processing of maintenance logs, sensor data analysis, and reinforcement learning to create self-healing power networks that can anticipate failures and automatically adjust resource allocation.

A novel framework combining LLM-based reasoning with reinforcement learning to optimize microgrid energy management while adapting to real-world uncertainties. The system uses natural language processing to interpret complex grid conditions and environmental factors, then employs multi-agent RL to coordinate distributed energy resources and storage systems.

A novel system that combines LLM-based multi-agent systems with wireless power transfer networks to create resilient, self-optimizing power distribution systems. The system continuously adapts to failures, misalignments, and changing power demands while maintaining optimal efficiency through intelligent agent coordination.

A novel framework combining large language models and formation control for surgical robot swarms, enabling real-time adaptation to dynamic surgical environments. The system uses LLM reasoning capabilities to interpret surgical context and guide precise multi-robot coordination while maintaining safety constraints.