Publications
Conference papers
- Mingtian Shao, Ruibo Wang, Wenzhe Zhang, Kai Lu, Yiqin Dai, Huijun Wu (corresponding author). From Islands to Archipelago: Towards Collaborative and Adaptive Burst Buffer for HPC Systems. Accepted by ACM ICS 2025 (CCF-B). [Paper]
- Wanxin Wang, Huijun Wu (corresponding author), Lihua Yang, Zhangyu Liu and Bin Zheng. AIO:Automating I/O Optimization Pipeline for Data-Intensive Applications in HPC. ISPA 2024 (CCF-C). [Paper]
- Xihong Yang, Erxue Min, Ke Liang, Yue Liu, Siwei Wang, Sihang Zhou, Huijun Wu, Xinwang Liu, En Zhu: GraphLearner: Graph Node Clustering with Fully Learnable Augmentation. ACM MM 2024 (CCF-A). [Paper]
- Huimin Ma, Siwei Wang, Shengju Yu, Suyuan Liu, Jun-Jie Huang, Huijun Wu, Xinwang Liu, En Zhu: Automatic and Aligned Anchor Learning Strategy for Multi-View Clustering. ACM MM 2024 (CCF-A). [Paper]
- Mingtian Shao, Wenzhe Zhang, Ruibo Wang, Huijun Wu, Yiqin Dai and Kai Lu. Fully Decentralized Data Distribution for Exascale-HPC: End of the Provider-Demander Matching Puzzle. CLUSTER 2024 (CCF-B). [Paper]
- Duanyu Li, Huijun Wu (corresponding author), Min Xie, Xugang Wu, Zhenwei Wu and Wenzhe Zhang. Talos: A More Effective and Efficient Adversarial Defense for GNN Models Based on the Global Homogeneity of Graphs. ECAI 2024 (CCF-B). [Paper]
- Zhangyu Liu, Cheng Zhang, Huijun Wu, Jianbin Fang, Lin Peng, Guixin Ye, Zhanyong Tang. Optimizing HPC I/O Performance with Regression Analysis and Ensemble Learning. CLUSTER 2023 (CCF-B). [Paper]
- Xugang Wu, Huijun Wu, Ruibo Wang, Duanyu Li, Xu Zhou, Kai Lu. Leveraging free labels to power up heterophilic graph learning in weakly-supervised settings: An empirical study. ECML/PKDD 2023 (CCF-B). [Paper]
- Huijun Wu, Chen Wang, Yuriy Tyshetskiy, Andrew Docherty, Kai Lu, Liming Zhu. Adversarial examples on graph data: Deep insights into attack and defense. IJCAI 2019 (CCF-A, selected as the most influential paper at IJCAI 2019 by papersdigest.org and has been cited 426 times as of July 2024). [Paper]
- Rimmal Nadeem, Huijun Wu, Hye-young Paik, Chen Wang. A case based deep neural network interpretability framework and its user study. WISE 2019 (CCF-C). [Paper]
- Huijun Wu, Chen Wang, Kai Lu, Yinjin Fu, Liming Zhu. One size does not fit all: The case for chunking configuration in backup deduplication. CCGrid 2018 (CCF-C). [Paper]
- Huijun Wu, Chen Wang, Jie Yin, Kai Lu, Liming Zhu. Sharing deep neural network models with interpretation. WWW 2018 (CCF-A). [Paper]
- Dongyao Wu, Sherif Sakr, Liming Zhu, Sung Lee, Huijun Wu. HDM-MC in-Action: A framework for big data analytics across multiple clusters. ICDCS 2018 (CCF-B,Demo). [Paper]
- Huijun Wu, Chen Wang, Yinjin Fu, Sherif Sakr, Liming Zhu, Kai Lu. Hpdedup: A hybrid prioritized data deduplication mechanism for primary storage in the cloud. MSST 2017 (CCF-B). [Paper]
- Dongyao Wu, Sherif Sakr, Liming Zhu, Huijun Wu. Towards big data analytics across multiple clusters. CCGrid 2017 (CCF-C). [Paper]
Journal papers
- Zhangyu Liu, Jinqiu Wang, Huijun Wu, Qingzhen Ma, Lin Peng, Zhanyong Tang. Auto-tuning for HPC storage stack: an optimization perspective. CCF Transactions on High Performance Computing (2024) CCF-C).[Paper]
- Xugang Wu, Huijun Wu, Ruibo Wang, Xu Zhou, Kai Lu.Towards adaptive graph neural networks via solving prior-data conflicts. Frontiers of Information Technology & Electronic Engineering (2024) (CCF-C).[Paper]
- Xugang Wu, Huijun Wu, Xu Zhou, Xiang Zhao, Kai Lu. Towards defense against adversarial attacks on graph neural networks via calibrated co-training. Journal of Computer Science and Technology (2022) (CCF-B).[Paper]
- Huijun Wu, Chen Wang, Richard Nock, Wei Wang, Jie Yin, Kai Lu, Liming Zhu. SMINT: Toward interpretable and robust model sharing for deep neural networks. ACM Transactions on the Web (2020) (CCF-B). [Paper]
- Huijun Wu, Chen Wang, Yinjin Fu, Sherif Sakr, Kai Lu, Liming Zhu. A differentiated caching mechanism to enable primary storage deduplication in clouds. IEEE Transactions on Parallel and Distributed Systems (2018) (CCF-A). [Paper]
- 王睿伯, 吴振伟, 张文喆, 邬会军, 张于舒晴, 卢凯. 基于内存保护键值的细粒度访存监控. 计算机工程与科学 (2024)(CCF-C(中文)).[Paper]