Haonan Yuan

Haonan Yuan

Final-month Ph.D.

Beihang University

Research Interests

Graph Machine Learning
Graph Foundation Model
Graph-oriented LLMs and Agents

About

I am a final-month Ph.D. candidate in the School of Computer Science and Engineering at Beihang University, advised by Prof. Jianxin Li and Prof. Qingyun Sun. I am also affiliated with Shen Yuan Honors College under the Top-notch Program of MoE. Prior to this, I received my B.Eng. degree in Software Engineering from the University of Electronic Science and Technology of China under the Excellent Engineer Education and Training Program of MoE.

My recent research explores graph machine learning, graph foundation models, and graph-oriented LLMs and agents. I am particularly interested in applying graph intelligence techniques to real-world scenarios, including social network analysis, cybersecurity, etc.

I have published papers in leading international venues, including TPAMI, ICML, NeurIPS, ICLR, WWW, and AAAI. I am always happy to connect with researchers and students who share similar interests. Feel free to send me an email if interested to discuss or work together.

Selected Publications

View All

A Survey on Foundation Models for Structured Data: Tabular, Time Series, and Graphs

Qingyun Sun, Haonan Yuan, Yi Huang, Ziwei Zhang, Xingcheng Fu, Ruijie Wang, Haoyi Zhou, Jia Wu, Jianxin Li, Philip S. Yu

PreprintResearchGate 2026PaperSlidesCode

RAG-GFM: Overcoming In-Memory Bottlenecks in Graph Foundation Models via Retrieval-Augmented Generation

Haonan Yuan, Qingyun Sun, Jiacheng Tao, Xingcheng Fu, Jianxin Li

CCF AWWW 2026PaperSlidesCode

Is the Information Bottleneck Robust Enough? Towards Label-Noise Resistant Information Bottleneck Learning

Yi Huang, Qingyun Sun, Yisen Gao, Haonan Yuan, Xingcheng Fu, Jianxin Li

CCF AAAAI 2026PaperSlidesCode

Privacy Auditing of Multi-Domain Graph Pre-Trained Model Under Membership Inference Attacks

Jiayi Luo, Qingyun Sun, Yuecen Wei, Haonan Yuan, Xingcheng Fu, Jianxin Li

CCF AAAAI 2026PaperSlidesCode

SA²GFM: Enhancing Robust Graph Foundation Models with Structure-Aware Semantic Augmentation

Junhua Shi, Qingyun Sun, Haonan Yuan, Xingcheng Fu

CCF AAAAI 2026PaperSlidesCode

Towards Effective, Stealthy, and Persistent Backdoor Attacks Targeting Graph Foundation Models

Jiayi Luo, Qingyun Sun, Lingjuan Lyu, Ziwei Zhang, Haonan Yuan, Xingcheng Fu, Jianxin Li

CCF AAAAI 2026PaperSlidesCode

News

2026-05

A new survey on foundation models for structured data is now available on ResearchGate.

2026-03

Our work on path-aware GraphRAG is now available on arXiv.

2026-01

Our RAG-GFM paper has been accepted to WWW 2026 🎉

2026-01

We released a new survey on information-theoretic graph machine learning.

2025-11

Glad to share that 4 papers from our group have been accepted to AAAI 2026 🎉

2025-11

Our work on evolving graph learning has been accepted to IEEE TPAMI 🎉