Research Index

A novel system combining multi-agent LLMs and dynamic wireless power transfer to optimize real-time charging for autonomous EV fleets. The system uses predictive analytics to coordinate vehicle movements and charging infrastructure, while defending against potential cyber-attacks through secure multi-agent protocols.

A novel approach combining test-time reinforcement learning (TTRL) with microgrid energy management to create self-optimizing power systems. The system continuously learns from operational data without requiring explicit labels, enabling real-time adaptation to changing conditions while maintaining grid stability and optimizing energy usage patterns.