Shenghua Liu is a professor who is leading the BiG Team group, at Key Laboratory of Network Data Science and Technology, Institute of Computing Technology, CAS. He once visited at the University of California, Los Angeles, hosted by Prof. Lei He, and as a scholar at Carnegie Mellon University, hosted by Prof. Christos Faloutsos.

AGI fundamentally requires trustworthy model reasoning and high-quality data. His research interests include:

• trustworthy large foundation model technologies, addressing critical challenges such as knowledge editing, contextual faithfulness, and safe generation.
• methodologies for constructing and governing high-quality data, including big graph mining, approximation algorithms, graph compression, and summarization techniques.

The arising of LLMs drives most of his interests to trustworthy foundation models, and graph LLMs which brings LLM the ability to understand grpahs, think and model with graphs. With graph LLMs, real world complex and combination problems can be well and trustworthily solved by AGI. Two of about 60 high-quality publications have been recognized as the best paper award and candidate respectively.