个人简介：
万晨博士，2023年6月毕业于中山大学计算机学院，获博士学位，同年12月加入汕头大学计算机系，主要研究领域为AI安全。实验室配备3张RTX 3090与1张RTX 4090 GPU，算力充足。
指导研究生、本科生在对抗攻击与AI安全方向开展研究，多名学生在读期间以第一作者身份在ICASSP、Neurocomputing、SPL、ICIC等国际会议及期刊发表论文；所指导的本科生中，已有两名推免至电子科技大学，一人攻读硕士学位，一人直博。
欢迎对AI安全、对抗机器学习等方向感兴趣的本科生及拟报考硕士研究生与我联系，共同开展研究工作。
科研项目：
[1] 广东省自然科学基金面上项目，高阶梯度优化与多策略增强驱动的对抗样本迁移机制研究，2026.01-2028.12，10万元，主持。
[2] 中国高校产学研创新基金（AI+网络安全治理技术专项），AI视觉系统高迁移性对抗攻击与安全检测方法研究，2026.04-2027.03，20万元，主持。
[3] 汕头大学“人工智能+”高等教育教学改革项目，Python与人工智能：生成式AI与交互式教学改革，2025.06-2026.06，1万元，主持。
[4] 汕头大学科研启动基金项目，对抗样本优化方法研究，2024.01-2026.12，12.5万元，主持。
学术论文：
[1] Wutao Chen (研究生), Huaqin Zou (本科生), Chen Wan*, and Lifeng Huang. A two-stage globally-diverse adversarial attack for vision-language pre-training models. In IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2026. (CCF B 会议, 通讯作者, 已录用)
[2] Hailing Kuang (研究生), Chen Wan*, Yayin Zheng, Zihong Guo, and Wutao Chen. Bidirectional gradient optimization for enhancing adversarial transferability. Neurocomputing, vol. 669, 132503, 2026. (中科院SCI二区, 通讯作者)
[3] Xiaohai Lu (研究生), Chen Wan*, and Lifeng Huang. Improving the adversarial transferability via histogram transformation. IEEE Signal Processing Letters, vol. 32, pp. 3949–3953, 2025. (中科院SCI三区, CCF C期刊, 通讯作者)
[4] Zihong Guo (本科生), Chen Wan*, Yayin Zheng, Hailing Kuang, and Xiaohai Lu. Boosting adversarial transferability against defenses via multi-scale transformation. In International Conference on Intelligent Computing (ICIC), vol. 15847, pp. 502–513, 2025. (CCF C会议, Oral, 通讯作者)
[5] Yayin Zheng (本科生), Chen Wan*, Zihong Guo, Hailing Kuang, and Xiaohai Lu. Boosting adversarial transferability via high-frequency augmentation and hierarchical-gradient fusion. In International Conference on Intelligent Computing (ICIC), pp. 3323–3337, 2025. (CCF C会议, 通讯作者)
[6] Chen Wan, Fangjun Huang, and Xianfeng Zhao. Average gradient-based adversarial attack. IEEE Transactions on Multimedia, vol. 25, pp. 9572–9585, 2023. (中科院SCI一区, TOP, CCF A期刊)
[7] Chen Wan, Biaohua Ye, and Fangjun Huang. PID-based approach to adversarial attacks . In AAAI Conference on Artificial Intelligence (AAAI), pp. 10033–10040, 2021. (CCF A会议)
[8] 万晨, 黄方军. 基于龙格库塔法的对抗攻击方法. 软件学报, 35(5): 2543–2565, 2024. (CCF-T1期刊)
[9] Lifeng Huang, Han Wang, Chen Wan, Zusheng Zhang, Shaojian Qiu, and Qiong Huang. Improving transferability of data-free universal adversarial perturbations via auxiliary ensembles. IEEE Transactions on Multimedia, 2025, doi: 10.1109/TMM.2026.3676663. (中科院SCI一区, TOP, CCF A期刊)
[10] Chen Wan, Tao Li, Wu Zhang, and Jing Dong. Dynamics of epidemic spreading model with drug-resistant variation on scale-free networks. Physica A: Statistical Mechanics and its Applications, vol. 493, pp. 17–28, 2018. (SCI)
[11] Chen Wan, Tao Li, Zhihong Guan, Yuanmei Wang, and Xiongding Liu. Spreading dynamics of an e-commerce preferential information model on scale-free networks. Physica A: Statistical Mechanics and its Applications, vol. 467, pp. 192–200. (SCI)
[12] Chen Wan, Tao Li, and Zhicheng Sun. Global stability of a SEIR rumor spreading model with demographics on scale-free networks. Advances in Difference Equations, vol. 2017, p. 253, 2017. (SCI)
[13] Tao Li, Xiongding Liu, Jie Wu, Chen Wan, Zhihong Guan, and Yuanmei Wang. An epidemic spreading model on adaptive scale-free networks with feedback mechanism. Physica A: Statistical Mechanics and its Applications, vol. 450, pp. 649–656, 2016. (SCI)
[14] 黄方军, 万晨. JPEG图像重压缩检测综述. 信号处理, 37(12): 2251-2260, 2021. (中文核心)
[15] Fan Li, Chen Wan, and Fangjun Huang. Adaptive robust watermarking method based on deep neural networks. In International Workshop on Digital Watermarking (IWDW), pp. 162–173, 2022.
