I’m currently a Ph.D. candidate (2020 Fall - Now) in Computer Science and Engineering at the University of Notre Dame, advised by Prof. Fanny Ye. Before that, I received my M.S. degree from The Ohio State University, advised by Prof. Ping Zhang, and my B.S. degree from Xidian University.

My research field lies in graph machine learning and its application. Specifically, I enjoy doing research on semi-supervised and self-supervised representation learning via graph neural networks.

News

• [2024.05] One first-author paper is accepted by ICML’24.
• [2024.04] One first-author paper is accepted by UAI’24.
• [2023.10] I will serve as a PC member for WWW’24.
• [2023.07] One first-author paper is accepted by CIKM’23.
• [2023.07] I will serve as a PC member for NeurIPS’23.
• [2023.06] I will join Amazon SCOT as an applied scientist intern.
• [2023.05] One paper is accepted by ICML’23.
• [2023.01] One paper is accepted by ICLR’23.
• [2022.10] One first-author paper is accepted by WSDM’23.

Selected Publications

[Full List] [Google Scholar]

(* stands for equal contribution)

• From Coarse to Fine: Enable Comprehensive Graph Self-supervised Learning with Multi-granular Semantic Ensemble
  Qianlong Wen, Mingxuan Ju, Zhongyu Ouyang, Chuxu Zhang, Yanfang Ye
  [ICML’24] International Conference on Machine Learning

• GCVR: Reconstruction from Cross-View Enable Sufficient and Robust Graph Contrastive Learning
  Qianlong Wen, Zhongyu Ouyang, Chunhui Zhang, Yiyue Qian, Chuxu Zhang, Yanfang Ye
  [UAI’24] Uncertainty in Artificial Intelligence

• A Multi-Modality Framework for Drug-Drug Interaction Prediction by Harnessing Multi-source Data
  Qianlong Wen, Jiazheng Li, Chuxu Zhang, Yanfang Ye
  [CIKM’23] The ACM International Conference on Information and Knowledge Management

• When sparsity meets contrastive models: less graph data can bring better class-balanced representations
  Chunhui Zhang, Chao Huang, Yijun Tian, Qianlong Wen, Zhongyu Ouyang, Youhuan Li, Yanfang Ye, Chuxu Zhang
  [ICML’23] International Conference on Machine Learning

• Multi-task Self-supervised Graph Neural Networks Enable Stronger Task Generalization
  Mingxuan Ju, Tong Zhao, Qianlong Wen, Wenhao Yu, Neil Shah, Yanfang Ye, Chuxu Zhang
  [ICLR’23] International Conference on Learning Representations

• Self-Supervised Graph Structure Refinement for Graph Neural Networks
  Jianan Zhao*, Qianlong Wen*, Mingxuan Ju, Yanfang Ye, Chuxu Zhang
  [WSDM’23] The ACM International Conference on Web Search and Data Mining

• Disentangled Dynamic Heterogeneous Graph Learning for Opioid Overdose Prediction
  Qianlong Wen, Zhongyu Ouyang, Jianfei Zhang, Yiyue Qian, Yanfang Ye, Chuxu Zhang
  [KDD’22] The ACM SIGKDD Conference on Knowledge Discovery and Data Mining

• Gophormer: Ego-Graph Transformer for Node Classification
  Jianan Zhao*, Chaozhuo Li, Qianlong Wen*, Yiqi Wang, Yuming Liu, Hao Sun, Xing Xie, Yanfang Ye
  Arxiv Preprint, 2021

• Multi-view Self-supervised Heterogeneous Graph Embedding
  Jianan Zhao, Qianlong Wen, Shiyu Sun, Yanfang Ye, Chuxu Zhang
  [ECML/PKDD’21] European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases

Contact

• Email: qwen [at] nd [dot] edu
• Office: 247 Fitzpatrick Hall of Engineering
• Location: University of Notre Dame, Notre Dame, IN 46565