- Fatemeh Aminzadeh*, Jun Wu*, Jingrui He, Morteza Saberi, and Fatemeh Vafaee. Single-Cell Data Integration and Cell Type Annotation through Contrastive Adversarial Open-set Domain Adaptation. Genomics, Proteomics & Bioinformatics (accepted).
- Jun Wu, and Jingrui He. Trustworthy Transfer Learning: A Survey. Journal of Artificial Intelligence Research (accepted).
- Emma Tong, Sophia Chen, and Jun Wu. NoNitro: A UAV- and AI-Empowered Integrated System for Soil Nitrate Control. PRAI 2025.
- Xinyue Zeng, Haohui Wang, Junhong Lin, Jun Wu, Tyler Cody, and Dawei Zhou. LensLLM: Unveiling Fine-Tuning Dynamics for LLM Selection. ICML 2025.
- Katherine Tieu, Dongqi Fu, Jun Wu, and Jingrui He. Invariant Link Selector for Spatial-Temporal Out-of-Distribution Problem. AISTATS 2025.
- Jun Wu, Jingrui He, and Hanghang Tong. Distributional Network of Networks for Modeling Data Heterogeneity. KDD 2024.
- Wenxuan Bao, Jun Wu, and Jingrui He. BOBA: Byzantine-Robust Federated Learning with Label Skewness. AISTATS 2024.
- Jun Wu, Elizabeth Ainsworth, Andrew Leakey, Haixun Wang, and Jingrui He. Graph-Structured Gaussian Processes for Transferable Graph Learning. NeurIPS 2023.
- Jun Wu, and Jingrui He. Trustworthy Transfer Learning: Transferability and Trustworthiness. KDD 2023.
- Jun Wu, Wenxuan Bao, Elizabeth Ainsworth, and Jingrui He. Personalized Federated Learning with Parameter Propagation. KDD 2023.
- Wenxuan Bao, Haohan Wang, Jun Wu, and Jingrui He. Optimizing the Collaboration Structure in Cross-Silo Federated Learning. ICML 2023.
- Jun Wu, Jingrui He, and Elizabeth Ainsworth. Non-IID Transfer Learning on Graphs. AAAI 2023.
- Jun Wu, and Jingrui He. A Unified Framework for Adversarial Attacks on Multi-Source Domain Adaptation. TKDE 2023.
- Jun Wu, Jingrui He, Sheng Wang, Kaiyu Guan, and Elizabeth Ainsworth. Distribution-Informed Neural Networks for Domain Adaptation Regression. NeurIPS 2022.
- Jun Wu, and Jingrui He. Domain Adaptation with Dynamic Open-Set Targets. KDD 2022.
- Jun Wu, and Jingrui He. A Unified Meta-Learning Framework for Dynamic Transfer Learning. IJCAI 2022.
- Jun Wu, Hanghang Tong, Elizabeth Ainsworth, and Jingrui He. Adaptive Knowledge Transfer on Evolving Domains. IEEE BigData 2022.
- Jun Wu, and Jingrui He. Dynamic Transfer Learning with Progressive Meta-task Scheduler. Frontiers in Big Data 2022.
- Yao Zhou*, Jun Wu*, Haixun Wang, and Jingrui He. Adversarial Robustness through Bias Variance Decomposition: A New Perspective for Federated Learning. CIKM 2022.
- Jun Wu, and Jingrui He. Indirect Invisible Poisoning Attacks on Domain Adaptation. KDD 2021.
- Yao Zhou, Jianpeng Xu, Jun Wu, Zeinab Taghavi, Evren Korpeoglu, Kannan Achan, and Jingrui He. PURE: Positive-Unlabeled Recommendation with Generative Adversarial Network. KDD 2021.
- Jun Wu, and Jingrui He. Scalable Manifold-Regularized Attributed Network Embedding via Maximum Mean Discrepancy. CIKM 2019.
- Jun Wu, Jingrui He, and Jiejun Xu. DEMO-Net: Degree-Specific Graph Neural Networks for Node and Graph Classification. KDD 2019.
- Jun Wu, Jingrui He, and Yongming Liu. Imverde: Vertex-Diminished Random Walk for Learning Imbalanced Network Representation. IEEE BigData 2018.
