主要研究兴趣为：对抗学习，人工智能安全，深度学习，计算机视觉

近年来，在包括IEEE Transactions on Image Processing、IEEE Conference on Computer Vision and Pattern Recognition（CVPR）、 Pattern Recognition、软件学报等本领域顶级期刊和学术会议发表论文多篇，并获得国家专利授权多项。详细介绍请点这里。

如果你对人工智能、深度学习和对抗学习攻防相关领域感兴趣并想进一步探索，欢迎各位本科生联系我/报考我的研究生：huanglf6@scau.edu.cn

2022.07-今  华南农业大学  数学与信息学院  讲师

2018.09-2022.06  中山大学  计算机学院  博士

2012.09-2015.06  中山大学  计算机学院  硕士

2008.09-2012.06  西南交通大学  信息科学与技术学院  学士

Lifeng Huang, Qiong Huang, Peichao Qiu, Shuxin Wei, Chengying Gao. FASTEN: Fast Ensemble Learning For Improved Adversarial Robustness. IEEE Transactions on Information Forensics and Security (TIFS 2023). [CCF-A/SCI中科院1区Top] [Code]

Lifeng Huang, Chengying Gao, Ning Liu. Erosion Attack: Harnessing Corruption To Improve Adversarial Examples. IEEE Transactions on Image Processing (TIP 2023). [CCF-A/SCI中科院1区Top] [Code]

Lifeng Huang, Chengying Gao, Ning Liu. DEFEAT: Decoupled feature attack across deep neural networks. Neural Networks (NN 2022). [CCF-B/SCI中科院1区Top] [Code]

Lifeng Huang, Shuxin Wei, Chengying Gao, Ning Liu. Cyclical Adversarial Attack Pierces Black-box Deep Neural Networks. Pattern Recognition (PR 2022). [CCF-B/SCI中科院1区Top] [Code]

黄立峰, 庄文梓, 廖泳贤, 刘宁.  一种基于进化策略和注意力机制的黑盒对抗攻击算法. 软件学报, 2021, 32(11): 3512-3529. [CCF-A中文/北大核心]

Lifeng Huang, Chengying Gao, Yuyin Zhou, Changqing Zou, Cihang Xie, Alan Yuille, Ning Liu. Universal Physical Camouflage Attacks on Object Detectors. Proc. IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2020: 720-729. [CCF-A] [Code]

Lifeng Huang, Chengying Gao, Wenzi Zhuang, Ning Liu. Enhance Transferable Adversarial Examples Via Self-Augmentation. Proc. International Conference on Multimedia and Expo (ICME Oral). [CCF-B] [Code]

Ying Chen, Lifeng Huang, Chengying Gao, Ning Liu. Scale-aware Progressive Optimization Network. Proc. ACM International Conference on Multimedia (ACM MM), 2020: 2211-2219. [CCF-A]

Xing wu, Lifeng Huang, Chengying Gao.  G-UAP: Generic Universal Adversarial Perturbation that Fools RPN-based Detectors. Proc. Asian Conference on Machine Learning (ACML), PMLR, 2019: 1204-1217. [CCF-C]

陈君, 黄立峰, 高成英, 吴贺丰.  基于Gabor小波加权组合特征的性别识别. 计算机辅助设计与图形学学报, 2015, 27(9): 1767-1774. [CCF-A中文/北大核心]