Welcome! 👋

I am a first-year Ph.D. student in Computer Science at The Chinese University of Hong Kong, Shenzhen (CUHK-Shenzhen), where I am privileged to be advised by Prof. Zhongxiang Dai. My research interests lie at the intersection of Large Language Models (LLMs) and Reinforcement Learning.

Prior to my doctoral studies, I served as a Research Assistant in the same group. I earned my Bachelor’s degree in Computer Science from Lanzhou University. For academic collaborations or inquiries, please feel free to reach me at mingzekong@cuhk.edu.cn.

Research Interests

• 🤖 Multi-Agent Systems: Exploring coordination, communication, and collaboration mechanisms among multiple intelligent agents to solve complex tasks in dynamic environments.
• 🧠 Large Language Model (LLM) Agents: Investigating how LLMs can act as autonomous decision-makers and reasoners, enabling them to plan, execute, and adapt in diverse real-world scenarios.
• 🎮 Reinforcement Learning (RL): Developing algorithms that enable agents to learn optimal policies through interaction with environments, with a focus on sample efficiency and generalization.
• 🎰 Multi-Armed Bandit (MAB) Problems: Advancing both theoretical foundations and practical applications of bandit algorithms, focusing on efficient exploration-exploitation trade-offs in uncertain and dynamic environments.

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