Research & Publications

Graph AI Development

Publications

Dongqi Fu, Zhigang Hua, Yan Xie, Jin Fang, Si Zhang, Kaan Sancak, Hao Wu, Andrey Malevich, Jingrui He, and Bo Long. VCR-Graphormer: A Mini-batch Graph Transformer via Virtual Connections. The 12th International Conference on Learning Representations (ICLR 2024), May 2024. [Paper] [Poster] [Code]
Dongqi Fu. Investigating Natural and Artificial Dynamics in Graph Data Mining and Machine Learning. The 32nd ACM International Conference on Information and Knowledge Management (CIKM 2023), October 2023. (Doctoral Symposium) [Paper]
Dongqi Fu*, Wenxuan Bao*, Ross Maciejewski, Hanghang Tong, Jingrui He. Privacy-Preserving Graph Machine Learning from Data to Computation: A Survey. SIGKDD Explorations, June 2023. (*Equal Contribution). [Paper]
Dongqi Fu, Dawei Zhou, Ross Maciejewski, Arie Croitoru, Marcus Boyd, and Jingrui He. Fairness-Aware Clique-Preserving Spectral Clustering of Temporal Graphs. The ACM Web Conference 2023 (WWW 2023), April 2023. [Paper] [Slides] [Code]
Zihao Li*, Dongqi Fu*, and Jingrui He. Everything Evolves in Personalized PageRank. The ACM Web Conference 2023 (WWW 2023), April 2023. (*Equal Contribution). [Paper] [Slides] [Code]
Dongqi Fu, Zhe Xu, Hanghang Tong, and Jingrui He. Natural and Artificial Dynamics in GNNs: A Tutorial. The 16th ACM International Conference on Web Search and Data Mining (WSDM 2023), February 2023. (Tutorial) [Paper] [Slides]
Dongqi Fu and Jingrui He. DPPIN: A Biological Repository of Dynamic Protein-Protein Interaction Network Data. 2022 IEEE International Conference on Big Data (IEEE BigData 2022), December 2022. [Paper] [Slides] [Video] [Data&Code]
Dongqi Fu and Jingrui He. Natural and Artificial Dynamics in Graphs: Concept, Progress, and Future. Frontiers in Big Data, December 2022. [Paper]
Dawei Zhou*, Lecheng Zheng*, Dongqi Fu, Jiawei Han, and Jingrui He. MentorGNN: Deriving Curriculum for Pre-Training GNNs. The 31st ACM International Conference on Information and Knowledge Management (CIKM 2022), October 2022. (*Equal Contribution). [Paper] [Video] [Code]
Dongqi Fu, Yikun Ban, Hanghang Tong, Ross Maciejewski, and Jingrui He. DISCO: Comprehensive and Explainable Disinformation Detection. The 31st ACM International Conference on Information and Knowledge Management (CIKM 2022), October 2022. [Paper] [Slides] [Demo] [Code]
Dongqi Fu, Jingrui He, Hanghang Tong, and Ross Maciejewski. Privacy-preserving Graph Analytics: Secure Generation and Federated Learning. Workshop on Privacy Enhancing Technologies for the Homeland Security Enterprise (PETS4HSE 2022), June 2022. [Paper] [Slides]
Dongqi Fu*, Liri Fang*, Ross Maciejewski, Vetle I Torvik, and Jingrui He. Meta-Learned Metrics over Multi-Evolution Temporal Graphs. The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2022), August 2022. (*Equal Contribution). [Paper] [Slides] [Video] [Code]
Dongqi Fu and Jingrui He. SDG: A Simplified and Dynamic Graph Neural Network. The 44th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2021), July 2021. [Paper] [Slides] [Video] [Code]
Dongqi Fu*, Zhe Xu*, Bo Li, Hanghang Tong, and Jingrui He. A View-Adversarial Framework for Multi-View Network Embedding. The 29th ACM International Conference on Information and Knowledge Management (CIKM 2020), October 2020. (*Equal Contribution). [Paper] [Slides] [Video] [Code]
Dongqi Fu, Dawei Zhou, and Jingrui He. Local Motif Clustering on Time-Evolving Graphs. The 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2020), August 2020. [Paper] [Slides] [Video] [Code]