I’m a Ph.D. Candidate in the School of Data Science at The Chinese University of Hong Kong, Shenzhen (CUHK-Shenzhen), advised by Prof. Yixiang Fang. Currently, i am a visiting scholar in NUS, mentored by Prof.Xiaokui Xiao. I am working closely with Prof. Chenhao Ma and Wensheng Luo. I got my Master degree from Harbin Institute of Technology Shenzhen in June 2022, under the supervision of Prof. Yunming Ye. Before that, I received my Bachelor’s degree from Harbin Institute of Technology in June 2020.

If all goes smoothly, I expect to graduate in January 2026 and begin my postdoctoral position in France shortly thereafter.

• 💬Wechat: JayL981001
• 📧Email: yinglizhou@link.cuhk.edu.cn or zhouyingli.hit@gmail.com

I am always open for possible collaborations, and visiting opportunities, please do not hesitate to contact me if you are interested!

Interests

My research interests mainly focus on large-scale data management and data mining, particularly graph data management and Large Language Models (LLMs) for data management. Specifically, my research spans the following topics:

• Data $\times$ LLM: efficient RAG systems and methods, memory management for LLM, and intelligent agent.
• Graph data management/mining: densest subgraph discovery, community search, clique listing/counting.
• AI4DB: latency prediction, cardinality estimation.

Yingli is working hard 😭😭😭 to produce impactful 🔥 and novel work 🌟. In addition, I am passionate about open-source communities and familiar with database kernels (such as TiDB).

LLM-based projects

1. Graph-based RAG system

• : DIGIMON

• : EraRAG

News

• 2025.09 💥💥 One paper is accepted by VLDB 2026! 😊
• 2025.08 💥💥 One paper is accepted by SIGMOD 2026! One paper is accepted by VLDB 2026!
• 2025.06 💥💥 Two papers are accepted by VLDB LLM + Graph Workshop 2025! Our new work about the graph-based RAG on dynamic corpus is available on arXiv! [arXiv]!
• 2025.06 💥💥 One Paper “Efficient 𝑘-Clique Densest Subgraph Discovery: Towards Bridging Practice and Theory” is accepted by VLDB 2025!
• 2025.03 💥💥 Our paper about the systemly benchmarck and analysis of graph-based RAG is available on arXiv! [arXiv]!
• 2025.01 💥💥 One Paper “Efficient Historical Butterfly Counting in Large Temporal Bipartite Networks via Graph Structure-aware Index” is accepted by VLDB 2025!

🌟 Personal Information

• Idols: Jay Chou (Music), Steve Jobs, and Cristiano Ronaldo

• Favorite Songs: 轨迹 (Chinese) and Something Just Like This (English)

• Hobbies: I enjoy jogging in my free time — it helps me think and clear my mind.

• Favorite Quote: 最平凡日子，最卑微梦想. (Even in ordinary life, we should cherish our small yet sincere dreams — they give meaning to every day.)