Published over 50 papers in top-tier venues including ICML, NeurIPS, KDD, ICLR, CVPR, AAAI, IJCAI, IEEE TPAMI, and TKDE
2025: Paper on graph foundation model accepted by NeurIPS
2025: Paper on graph for science accepted by Genome Biology
2025: Paper on OOD Graph NAS accepted by KDD
2025: Survey on Graph OOD Generalization accepted by IEEE TPAMI
2025: Tutorial on Low-Distortion Graph Representation Learning accepted by IJCAI
2025: Workshop on Frontiers in Graph Machine Learning for the Large Model Era accepted by CIKM
2024: Paper 'LLM4DyG: Can LLMs Solve Spatial-Temporal Problems on Dynamic Graphs?' accepted by KDD
2020: Open-sourced AutoGL, an AutoML toolkit for graphs
Background
Associate professor in the School of Computer Science and Engineering, Beihang University
Research interests lie at the intersection of graph machine learning and large language models (LLMs), including graph foundation models, Graph LLMs, GraphRAG, Graph Agents, and graph-enhanced LLM reasoning
Seeking self-motivated undergraduate interns and master's students with strong mathematical and coding skills
The research group has several master’s and PhD positions available each year
Open to collaborations and discussions on graph machine learning topics