Jie-Jing Shao

Jie-Jing Shao 邡杰晢

Ph.D., Incoming Researcher, A*STAR CFAR, Singapore

I am an incoming researcher at A*STAR CFAR, as part of the AGI pillar.

I finished my Ph.D. at Nanjing University, advised by Prof. Yu-Feng Li, and was a member of LAMDA Group, led by Prof. Zhi-Hua Zhou.

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Our long-term goal is to build general and robust AI agents that contribute to the advancement of artificial general intelligence (AGI), enhance social productivity, and improve people's well-being. Our core approach centers on neuro-symbolic learning, which bridges data-driven learning with symbolic-driven search and 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.

Recently, my research has primarily focused on improving the generalization and data efficiency of Large Language Model-driven Agentic Systems, with the aim of advancing research on open scientific problems.

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