Publications

• Xi Chen, Wei Huang†, Ziwen Peng, Wei Guo, Fan Zhang. “Diversity Supporting Robustness: Enhancing Adversarial Robustness via Differentiated Ensemble Predictions.” Computers & Security (COSE), 2024.
• Huang, Wei, Yifan Zhou, Gaojie Jin, Youcheng Sun, Jie Meng, Fan Zhang, and Xiaowei Huang. “Formal Verification of Robustness and Resilience of Learning-Enabled State Estimation Systems.” Neurocomputing, 2024.
• Kaikang Zhao, Xi Chen, Wei Huang†, Liuxin Ding, Xianglong Kong, Fan Zhang. “Ensemble Adversarial Defense via Integration of Multiple Dispersed Low Curvature Models.” IJCNN, 2024.
• Xinwei Yuan, Shu Han, Wei Huang†, Hongliang Ye, Xianglong Kong, Fan Zhang. “A Simple Framework to Enhance the Adversarial Robustness of Deep Learning-based Intrusion Detection System.” Computers & Security (COSE), 2023.

• Huang, Wei, Xingyu Zhao, Alec Banks, Victoria Cox, Xiaowei Huang. “Hierarchical Distribution-Aware Testing of Deep Learning.” ACM Transactions on Software Engineering and Methodology (TOSEM), 2023.

• Huang, Wei, Xingyu Zhao, Gaojie Jin, and Xiaowei Huang. “SAFARI: Versatile and Efficient Evaluations for Robustness of Interpretability.” In Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV), 2023.

• Dong, Yi*, Wei Huang*, Vibhav Bharti, Victoria Cox, Alec Banks, Sen Wang, Xingyu Zhao, Sven Schewe, and Xiaowei Huang. “Reliability assessment and safety arguments for machine learning components in system assurance.” ACM Transactions on Embedded Computing Systems (TECS) 22, no. 3 (2023): 1-48.

• Jin, Gaojie, Xinping Yi, Wei Huang, Sven Schewe, and Xiaowei Huang. “Enhancing adversarial training with second-order statistics of weights.” In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 15273-15283. 2022.

• Huang, Wei, Xingyu Zhao, and Xiaowei Huang. “Embedding and extraction of knowledge in tree ensemble classifiers.” Machine Learning (2022): 1-34.

• Zhao, Xingyu, Wei Huang, Xiaowei Huang, Valentin Robu, and David Flynn. “Baylime: Bayesian local interpretable model-agnostic explanations.” In Uncertainty in artificial intelligence (UAI), pp. 887-896. PMLR, 2021.

• Huang, Wei, Youcheng Sun, Xingyu Zhao, James Sharp, Wenjie Ruan, Jie Meng, and Xiaowei Huang. “Coverage-guided testing for recurrent neural networks.” IEEE Transactions on Reliability 71, no. 3 (2021): 1191-1206.

• Zhao, Xingyu, Wei Huang, Sven Schewe, Yi Dong, and Xiaowei Huang. “Detecting operational adversarial examples for reliable deep learning.” In 2021 51st Annual IEEE/IFIP International Conference on Dependable Systems and Networks-Supplemental Volume (DSN-S), pp. 5-6. IEEE, 2021.

• Huang, Wei, Yifan Zhou, Youcheng Sun, James Sharp, Simon Maskell, and Xiaowei Huang. “Practical verification of neural network enabled state estimation system for robotics.” In 2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pp. 7336-7343. IEEE, 2020.

Worshop Papers

• Zhao, Xingyu, Wei Huang, Alec Banks, Victoria Cox, David Flynn, Sven Schewe, and Xiaowei Huang. “Assessing the reliability of deep learning classifiers through robustness evaluation and operational profiles.” In AISafety’21 Workshop at IJCAI’21 (Best Paper Award).

• Qi, Yi, Philippa Ryan Conmy, Wei Huang, Xingyu Zhao, and Xiaowei Huang. “A hierarchical HAZOP-like safety analysis for learning-enabled systems.” In AISafety’22 Workshop at IJCAI’22.

* signifies equal contributions and † represents corresponding author. You can also find my articles on my Google Scholar profile