Agentic & Multimodal AI

I study architectures that combine multimodal perception with planning, retrieval, and tool use. The goal is to build agents that can ground their reasoning in real environments and make their decisions more transparent and dependable.

This work includes multimodal large language models, retrieval-augmented generation, multi-agent systems, and evaluation methods for real-world tasks.