| 2026 | NDSS | Achieving Interpretable DL-based Web Attack Detection through Malicious Payload Localization. | Peiyang Li, Fukun Mei, Ye Wang, Zhuotao Liu, Ke Xu, Chao Shen, Qian Wang, Qi Li |
| 2025 | CCS | Training Robust Classifiers for Classifying Encrypted Traffic under Dynamic Network Conditions. | Yuqi Qing, Qilei Yin, Xinhao Deng, Xiaoli Zhang, Peiyang Li, Zhuotao Liu, Kun Sun, Ke Xu, Qi Li |
| 2025 | ICASSP | Robust Supervised Graph Embedding Method For EEG-Based Brain Network Emotion Recognition. | Pengcheng Zhu, Cunbo Li, Peiyang Li, Fali Li, Dezhong Yao, Peng Xu |
| 2024 | AAAI | Lifting by Image - Leveraging Image Cues for Accurate 3D Human Pose Estimation. | Feng Zhou, Jianqin Yin, Peiyang Li |
| 2024 | IWQoS | Enhancing Fraud Transaction Detection via Unlabeled Suspicious Records. | Ye Wang, Yunpeng Liu, Ningtao Wang, Peiyang Li, Jiahao Hu, Xing Fu, Weiqiang Wang, Kun Sun, Qi Li, Ke Xu |
| 2023 | CCS | Learning from Limited Heterogeneous Training Data: Meta-Learning for Unsupervised Zero-Day Web Attack Detection across Web Domains. | Peiyang Li, Ye Wang, Qi Li, Zhuotao Liu, Ke Xu, Ju Ren, Zhiying Liu, Ruilin Lin |
| 2023 | SEKE | CAPS: An Efficient Whole-Program Critical Paths Search Framework for Large-Scale Software. | Peiyang Li, Zixin Liu, Yuening Su, Hao Wang, Bo Jiang |
| 2023 | TASE | OAT: An Optimized Android Testing Framework Based on Reinforcement Learning. | Mengjun Du, Peiyang Li, Lian Song, W. K. Chan, Bo Jiang |
| 2022 | ESORICS | Verifying the Quality of Outsourced Training on Clouds. | Peiyang Li, Ye Wang, Zhuotao Liu, Ke Xu, Qian Wang, Chao Shen, Qi Li |
| 2018 | CVPR | Deep Progressive Reinforcement Learning for Skeleton-Based Action Recognition. | Yansong Tang, Yi Tian, Jiwen Lu, Peiyang Li, Jie Zhou |
| 2016 | APSCC | Optimizational Methods for Index Construction on Big Graphs. | Peiyang Li, Xia Xie, Hai Jin, Hanhua Chen, Xijiang Ke |