| 2023 | SIGIR | Contrastive State Augmentations for Reinforcement Learning-Based Recommender Systems. | Zhaochun Ren, Na Huang, Yidan Wang, Pengjie Ren, Jun Ma, Jiahuan Lei, Xinlei Shi, Hengliang Luo, Joemon M. Jose, Xin Xin |
| 2022 | KDD | Debiasing Learning for Membership Inference Attacks Against Recommender Systems. | Zihan Wang, Na Huang, Fei Sun, Pengjie Ren, Zhumin Chen, Hengliang Luo, Maarten de Rijke, Zhaochun Ren |
| 2019 | TrustCom | Deep Android Malware Classification with API-Based Feature Graph. | Na Huang, Ming Xu, Ning Zheng, Tong Qiao, Kim-Kwang Raymond Choo |
| 2018 | TrustCom | A Novel Method for Detecting Image Forgery Based on Convolutional Neural Network. | Na Huang, Jingsha He, Nafei Zhu |
| 2016 | CIS | On the Recoverability of Data in Android YAFFS2. | Yameng Li, Jingsha He, Na Huang, Chengyue Chang |
| 2016 | ICARCV | Distributed event-triggered containment control of multiple rigid bodies with combinational measurements. | Na Huang, Zhisheng Duan, Changbin Yu |
| 2015 | ICA3PP | A Clustering Algorithm Based on Rough Sets for the Recommendation Domain in Trust-Based Access Control. | Bin Zhao, Jingsha He, Xinggang Xuan, Yixuan Zhang, Na Huang |