刘艾
硕士生导师
教师姓名:刘艾
教师拼音名称:Liu Ai
电子邮箱:
所在单位:计算机科学与技术学院/人工智能学院/软件学院
职务:Associate Professor
学历:博士毕业
性别:男
联系方式:shaoai@nuaa.edu.cn
学位:理学博士学位
职称:副教授
毕业院校:北京大学
所属院系:计算机科学与技术学院/软件学院
招生学科专业:
软件工程 -- 【招收硕士研究生】 -- 计算机科学与技术学院
电子信息 -- 【招收硕士研究生】 -- 计算机科学与技术学院
电子信息 -- 【招收硕士研究生】 -- 计算机科学与技术学院

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- Kaicheng Shao,,Yuteng Lu,Ai Liu,Meng Sun.Diagnosing Deep Learning Errors with Reinforcement Learning-Driven Adversarial Examples:accepted by QRS 2025
- Ai Liu,,Yang Liu,Shaoying Liu,Zhibin Yang.Testing-Based Formal Verification with Program Slicing on Functional Soundness and Completeness.[C]:Proceedings of TASE 2025,2025:11-29
- Ai Liu,,Yang Liu,Shaoying Liu.TBFV4J: An Automated Testing-Based Formal Verification Tool for Java.[C]:ISSTA Companion '25: Proceedings of the 34th ACM SIGSOFT International Symposium on Software Testing and Analysis,2025:66-70
- Lei Rao,,Shaoying Liu,Ai Liu.Program Segment Testing for Human–Machine Pair Programming.[J]:International Journal of Software Engineering and Knowledge Engineering,2024,34(10):1565-1591
- Pingyan Wang,,Ai Liu,Shaoying Liu,Wen jiang.Detecting security vulnerabilities with vulnerability nets.[J]:Journal of Systems and Software,2024
- Haiyi Liu,,Shaoying Liu,Guangquan Xu,Ai Liu,Yujun Dai.Utilizing Testing-Based Formal Verification in Neural Networks: A Theoretical Approach.[C]:2023 13th International Conference on Software Technology and Engineering (ICSTE),2023:151-155
- Yujun Dai,,Shaoying Liu,Guangquan Xu,Ai Liu.Utilizing Risk Number and Program Slicing to Improve Human-Machine Pair Inspection.[C]:Proceedings of ICECCS 2023,2023:108-115
- Haiyi Liu,,Shaoying Liu,Guangquan Xu,Ai Liu,Dingbang Fang.NNTBFV: Simplifying and Verifying Neural Networks Using Testing-Based Formal Verification..[J]:International Journal of Software Engineering and Knowledge Engineering,2023,34(2)
- Pingyan Wang,,Shaoying Liu,Ai Liu,Weng Jiang.Detecting Security Vulnerabilities with Vulnerability Nets.[C]:Proceedings of QRS-Companion 2022,2023:375-383
- Haiyi Liu,,Shaoying Liu,Ai Liu,Dingbang Fang,Guangquan Xu.Verifying and Improving Neural Networks Using Testing-Based Formal Verification.[C]:Proceedings of SOFL+MSVL 2022,2023:126-141