LLM Agents, Multi-Agent Systems & Human-AI Interaction (Postdoc Collaboration)

I am a PhD candidate in Computer Science working on LLM-based agent systems, with a strong focus on conversational recommender systems, multi-agent architectures, and human-AI interaction.

My research explores how to design intelligent systems that support user decision-making under information overload, combining techniques from large language models, reinforcement learning (e.g., contextual bandits), and interactive AI. I am particularly interested in user-side AI systems that enhance autonomy, transparency, and rational decision processes.

I have experience developing multi-agent frameworks for conversational AI, integrating LLMs with structured reasoning, memory, and orchestration mechanisms. My work also touches on explainability, evaluation of interactive systems, and hybrid intelligence paradigms.

I am open to collaborations and MSCA postdoctoral opportunities in areas including (but not limited to):

• LLM-based agents and agentic AI

• Multi-agent systems and orchestration

• Conversational AI and recommender systems

• AI for scientific discovery

• Decision support systems

• Human-AI interaction and explainability

I am particularly interested in interdisciplinary environments and new domains where agent-based AI can be applied.