🤵🏻 About Me
I am a researcher with research interests in artificial intelligence and machine learning. I obtained my Ph.D. degree from Department of Computer Science and Technology in Nanjing University in June 2022, where I was very fortunate to be advised by professor Yu-Feng Li (李宇峰). Currently, I am an Assistant Professor in School of Intelligence Science and Technology, Nanjing University (Suzhou Campus). I am also a member of LAMDA Group (机器学习与数据挖掘研究所), which is led by professor Zhi-Hua Zhou (周志华).
📖 Research
The long-term research goal of our team is to enhance the reasoning and planning capabilities of AI models in both digital and physical worlds,
contributing to the advancement of artificial general intelligence (AGI). Our core approach is neuro-symbolic learning,
which bridges data-driven machine learning with knowledge-driven symbolic reasoning — often regarded as the hallmark of third-generation AI.
The neural component provides grounding in perception and physical interaction, while the symbolic component augments reasoning and planning.
How to bridge data-drive machine learning with knowledge-driven symbolic reasoning? Perceive the Environment via Multi-Modal Input Think, Reason, and Plan with the Environment Perception Take Actions to Change the Environment 📢: 招收对人工智能、大模型感兴趣，有较好编程基础的学生，可通过邮箱guolz@nju.edu.cn联系我，请附上带普通生活照的个人简历、成绩单。
Recently, our research has primarily focused on Multi-Modal Reasoning and Planning with (Multi-Modal) Large Language Models (e.g., LLM, VLM, VLA, VLN, etc.), addressing challenges across high-quality reasoning data construction, model training/fine-tuning via SFT and RL, and inference.
Potential applications include, but are not limited to, Visual Reasoning and Planning, Game Agent, Embodied Planning, Tool-Use/LLM-Agent, AI4Math, Domain-Specific Large Models, etc.
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