当前位置: X-MOL首页全球导师 国内导师 › 刘艾杉

个人简介

刘艾杉 ,博士,硕导,北京航空航天大学计算机学院助理教授。主要研究方向为可信赖人工智能、鲁棒深度学习、对抗攻防等,已在国际权威学术期刊和顶级会议等发表论文近50篇,申请专利20余项。荣获省部级科技进步二等奖1项(第三完成人)、腾讯犀牛鸟精英人才、BSIG优博提名、CCF百名优秀大学生等奖励。作为客座编辑在Pattern Recognition、Visual Intelligence等SCI期刊组织鲁棒深度学习专刊,担任国际顶级会议CVPR、AAAI和ACM Multimedia的workshop主席并组织十余次“智能安全”相关主题论坛和竞赛。作为主持人主持多项国家级科研项目,参与标准编制6项、白皮书编制4项、专著编写3本。研究成果被人民网、中国搜索等权威媒体专门报道,支撑和指导工业级模型鲁棒性评测和构建,助力开源社区算法安全评测,并支撑全球对抗攻防竞赛。

研究领域

可信赖人工智能、鲁棒深度学习、对抗攻防等

近期论文

查看导师最新文章 (温馨提示:请注意重名现象,建议点开原文通过作者单位确认)

Chapter: Deepfake in Metaverse Wenbo Zhou, Aishan Liu, Cihang Xie, Nenghai Yu Handbook of Metaverse, Springer, 2023. (To Appear) Chapter 8: Explainable Artificial Intelligence in Computer Vision Aishan Liu, Xianglong Liu, Dacheng Tao Introduction to Explainable Artificial Intelligence (可解释人工智能导论), 电子工业出版社, 2022. RUNNER: Responsible UNfair NEuron Repair for Enhancing Deep Neural Network Fairness Tianlin Li, Yue Cao, Jian Zhang, Shiqian Zhao, Yihao Huang, Aishan Liu, Qing Guo, Yang Liu International Conference on Software Engineering (ICSE), 2024. Towards Defending Multiple Lp-norm Bounded Adversarial Perturbations via Gated Batch Normalization Aishan Liu, Shiyu Tang, Xinyun Chen, Lei Huang, Haotong Qin, Xianglong Liu, Dacheng Tao International Journal of Computer Vision (IJCV), 2023. Isolation and Induction: Training Robust Deep Neural Networks against Model Stealing Attacks Jun Guo, Aishan Liu?, Xingyu Zheng, Siyuan Liang, Yisong Xiao, Yichao Wu, Xianglong Liu ACM Multimedia (ACM MM), 2023. Face Encryption via Frequency-Restricted Identity-Agnostic Attacks Xin Dong, Rui Wang, Siyuan Liang, Aishan Liu, Lihua Jing ACM Multimedia (ACM MM), 2023. Exploring Inconsistent Knowledge Distillation for Object Detection with Data Augmentation Jiawei Liang, Siyuan Liang?, Aishan Liu?, Ke Ma, Jingzhi Li, Xiaochun Cao ACM Multimedia (ACM MM), 2023. Faire: Repairing Fairness of Neural Networks via Neuron Condition Synthesis Tianlin Li, Xiaofei Xie, Jian Wang, Qing Guo Aishan Liu, Lei Ma, Yang Liu ACM Transactions on Software Engineering and Methodology (TOSEM), 2023. Latent Imitator: Generating Natural Individual Discriminatory Instances for Black-Box Fairness Testing Yisong Xiao, Aishan Liu?, Tianlin Li, Xianglong Liu? ACM SIGSOFT International Symposium on Software Testing and Analysis (ISSTA), 2023. FAIRER: Fairness As Decision Rational Alignment Tianlin Li, Qing Guo, Aishan Liu, Mengnan Du, Zhiming Li, Yang Liu International Conference on Machine Learning (ICML), 2023. Fairness via Group Contribution Matching Tianlin Li, Zhiming Li, Anran Li, Mengnan Du, Aishan Liu, Qing Guo, Guozhu Meng, Yang Liu International Joint Conference on Artificial Intelligence (IJCAI), 2023. Exploring the Relationship between Architectural Design and Adversarially Robust Generalization Aishan Liu*, Shiyu Tang*, Siyuan Liang*, Ruihao Gong, Boxi Wu, Xianglong Liu, Dacheng Tao IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2023. Towards Benchmarking and Assessing Visual Naturalness of Physical World Adversarial Attacks Simin Li, Shuning Zhang, Gujun Chen, Dong Wang, Pu Feng, Jiakai Wang, Aishan Liu, Xin Yi, Xianglong Liu IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2023. SysNoise: Exploring and Benchmarking Training-Deployment System Inconsistency Yan Wang*, Yuhang Li*, Ruihao Gong*, Aishan Liu*, Yanfei Wang, Jian Hu, Yongqiang Yao, Yunchen Zhang, Tianzi Xiao, Fengwei Yu, Xianglong Liu Conference on Machine Learning and Systems (MLSys), 2023. X-Adv: Physical Adversarial Object Attacks against X-ray Prohibited Item Detection Aishan Liu*, Jun Guo*, Jiakai Wang, Siyuan Liang, Renshuai Tao, Wenbo Zhou, Cong Liu, Xianglong Liu, Dacheng Tao USENIX Security Symposium (USENIX Security), 2023. A Comprehensive Evaluation Framework for Deep Model Robustness Jun Guo, Wei Bao, Jiakai Wang, Yuqing Ma, Xinghai Gao, Gang Xiao, Aishan Liu?, Jian Dong, Xianglong Liu, Wenjun Wu Pattern Recognition (PR), 2023. Improving Robust Fairness via Balance Adversarial Training Chunyu Sun, Chenye Xu, Chengyuan Yao, Siyuan Liang, Yichao Wu, Ding Liang, XiangLong Liu, Aishan Liu? AAAI Conference on Artificial Intelligence (AAAI), 2023. 面向深度强化学习的对抗攻防综述 Aishan Liu, Jun Guo, Simin Li, Yisong Xiao, Xianglong Liu, Dacheng Tao 计算机学报 (Chinese Journal of Computers), 2022. 智能系统全生命周期安全测试理论与方法 Jiakai Wang,Aishan Liu,Simin Li,Xianglong Liu, Wenjun Wu 智能安全 (Artificial Intelligence Security), 2022. Temporal Speciation Network for Few-Shot Object Detection Xiaowei Zhao, Xianglong Liu, Yuqing Ma, Shihao Bai, Yifan Shen, Zeyu Hao, Aishan Liu IEEE Transactions on Multimedia (IEEE TMM), 2022. Harnessing Perceptual Adversarial Patches for Crowd Counting Shunchang Liu, Jiakai Wang, Aishan Liu?, Yingwei Li, Yijie Gao, Xianglong Liu, Dacheng Tao ACM Conference on Computer and Communications Security (ACM CCS), 2022. Region-wise Generative Adversarial Image Inpainting for Large Missing Areas Yuqing Ma, Xianglong Liu, Shihao Bai, Aishan Liu, Dacheng Tao, Edwin Hancock IEEE Transactions on Cybernetics (IEEE TCYB), 2022. Generating Transferable Adversarial Examples against Vision Transformers Yuxuan Wang, Jiakai Wang, Zixin Yin, Ruihao Gong, Jingyi Wang, Aishan Liu, Xianglong Liu ACM Multimedia (ACM MM), 2022. Imitated Detectors: Stealing Knowledge of Black-box Object Detectors Siyuan Liang, Aishan Liu, Jiawei Liang, Longkang Li, Yang Bai, Xiaochun Cao ACM Multimedia (ACM MM), 2022. Few-shot X-ray Prohibited Item Detection: A Benchmark and Weak-feature Enhancement Network Renshuai Tao, tianbo Wang, Ziyang Wu, Cong Liu, Aishan Liu, Xianglong Liu ACM Multimedia (ACM MM), 2022. Defensive Patches for Robust Recognition in the Physical World Jiakai Wang, Zixin Yin, Pengfei Hu, Renshuai Tao, Haotong Qin, Xianglong Liu, Dacheng Tao, Aishan Liu IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2022. Exploring Endogenous Shift for Cross-domain Detection: A Large-scale Benchmark and Perturbation Suppression Network Renshuai Tao, Hainan Li, Tianbo Wang, Yanlu Wei, Yifu Ding, Bowei Jin, Hongping Zhi, Xianglong Liu, Aishan Liu IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2022. Revisiting Audio Visual Scene-Aware Dialog Aishan Liu, Huiyuan Xie, Xianglong Liu, Zixin Yin, Shunchang Liu NeuroComputing, 2022. BIBERT: Accurate Fully Binarized BERT Haotong Qin, Yifu Ding, Mingyuan Zhang, Qinghua Yan, Aishan Liu, Qingqing Dang, Ziwei Liu, Xianglong Liu International Conference on Learning Representations (ICLR), 2022. Universal Adversarial Patch Attack for Automatic Checkout using Perceptual and Attentional Bias Jiakai Wang*, Aishan Liu*, Xiao Bai, Xianglong Liu IEEE Transactions on Image Processing (IEEE TIP), 2021. Progressive Diversified Augmentation for General Robustness of DNNs: A Unified Approach Hang Yu, Aishan Liu?, Gengchao Li, Jichen Yang, Chongzhi Zhang IEEE Transactions on Image Processing (IEEE TIP), 2021. ARShoe: Real-Time Augmented Reality Shoe Try-on System on Smartphones Shan An, Guangfu Che, Jinghao Guo, Haogang Zhu, Junjie Ye, Fangru Zhou, Zhaoqi Zhu, Dong Wei, Aishan Liu, Wei Zhang ACM Multimedia (ACM MM), 2021. On the Guaranteed Almost Equivalence Between Imitation Learning From Observation and Demonstration Zhihao Cheng, Liu Liu, Aishan Liu, Hao Sun, Meng Fang, Dacheng Tao IEEE Transactions on Neural Networks and Learning Systems (IEEE TNNLS), 2021. Training Robust Deep Neural Networks via Adversarial Noise Propagation Aishan Liu, Xianglong Liu, Hang Yu, Chongzhi Zhang, Qiang Liu, Dacheng Tao IEEE Transactions on Image Processing (IEEE TIP), 2021. Dual Attention Suppression Attack: Generate Adversarial Camouflage in Physical World Jiakai Wang, Aishan Liu, Zixin Yin, Shunchang Liu, Shiyu Tang, Xianglong Liu IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2021. Interpreting and Improving Adversarial Robustness of Deep Neural Networks with Neuron Sensitivity Chongzhi Zhang*, Aishan Liu*, Xianglong Liu, Yitao Xu, Hang Yu, Yuqing Ma, Tianlin Li IEEE Transactions on Image Processing (IEEE TIP), 2020. Spatiotemporal Attacks for Embodied Agents Aishan Liu, Tairan Huang, Xianglong Liu, Yitao Xu, Yuqing Ma, Xinyun Chen, Stephen Maybank, Dacheng Tao European Conference on Computer Vision (ECCV), 2020. Bias-based Universal Adversarial Patch Attack for Automatic Check-out Aishan Liu, Jiakai Wang, Xianglong Liu, Bowen Cao, Chongzhi Zhang, Hang Yu European Conference on Computer Vision (ECCV), 2020. Understanding Adversarial Robustness via Critical Attacking Route Tianlin Li*, Aishan Liu*, Xianglong Liu, Yitao Xu, Chongzhi Zhang, Xiaofei Xie Information Sciences (INS), 2020. 人工智能安全与评测 刘艾杉, 王嘉凯, 刘祥龙 人工智能 (AI-View), 2020. 人工智能机器学习模型及系统的质量要素和测试方法 王嘉凯, 刘艾杉, 刘祥龙 信息技术与标准化, 2020. Few-shot Visual Learning with Contextual Memory and Fine-grained Calibration Yuqing Ma, Shihao Bai, Wei Liu, Qingyu Zhang, Aishan Liu , Weimin Chen, Xianglong Liu International Joint Conference on Artificial Intelligence (IJCAI), 2020. Transductive Relation-Propagation Network for Few-shot Learning Yuqing Ma, Xianglong Liu, Shihao Bai, Lei Wang, Dailan He, Aishan Liu International Joint Conference on Artificial Intelligence (IJCAI), 2020. Coarse-to-Fine Image Inpainting via Region-wise Convolutions and Non-Local Correlation Haotong Qin, Yifu Ding, Mingyuan Zhang, Qinghua Yan, Aishan Liu, Qingqing Dang, Ziwei Liu, Xianglong Liu International Joint Conference on Artificial Intelligence (IJCAI), 2019. Perceptual Sensitive GAN for Generating Adversarial Patches Aishan Liu, Xianglong Liu, Jiaxin Fan, Yuqing Ma, Anlan Zhang, Huiyuan Xie and Dacheng Tao AAAI Conference on Artificial Intelligence (AAAI), 2019.

推荐链接
down
wechat
bug