Yingli ZHOU
I will obtain my Ph.D. in late March 2026 from the School of Data Science at The Chinese University of Hong Kong, Shenzhen, advised by Prof. Yixiang Fang. After that, i will join Université Claude Bernard Lyon 1 (Lyon, France) as a postdoctoral researcher, supported by the ERC Advanced Grant GO-Y project, affiliated with CNRS LIRIS, where I will work with Prof. Angela Bonifati (ACM Fellow, SIGMOD Chair).
I received my M.Eng. and B.Eng. from Harbin Institute of Technology in 2022 and 2020 respectively, under the supervision of Prof. Yunming Ye. I was a visiting student at the National University of Singapore in 2025, where I worked with Prof. Xiaokui Xiao.
My research lies at the intersection of data management, graph mining, and large language models. I am broadly interested in graph-based RAG systems, LLM-powered data systems, and scalable graph mining algorithms.
I am open to collaborations, invited talks, and visiting opportunities. Please reach out via email.
Research Interests
My research interests mainly focus on data management, graph mining, and artificial intelligence over large-scale graph data, particularly graph-based LLM systems and scalable graph analytics, including graph-based RAG, graph memory, LLM-powered methods for data systems (e.g., dataset search, latency prediction), and graph mining algorithms with theoretical bounds, such as densest subgraph discovery, and so on.
Recent News
- February 2026: Two papers were accepted to SIGMOD 2026.
- January 2026: One paper was accepted to VLDB 2026.
- September 2025: One paper was accepted to VLDB 2026.
- August 2025: One paper was accepted to SIGMOD 2026, and one paper was accepted to VLDB 2026.
- June 2025: Our paper “Efficient k-Clique Densest Subgraph Discovery: Towards Bridging Practice and Theory” was accepted to VLDB 2025.
- March 2025: Our paper on the systematic benchmark and analysis of graph-based RAG became available on arXiv. [arXiv]