| Machine learning methods for wind turbine condition monitoring: A review A Stetco, F Dinmohammadi, X Zhao, V Robu, D Flynn, M Barnes, J Keane, ... Renewable energy 133, 620-635, 2019 | 803 | 2019 |
| BayLIME: Bayesian Local Interpretable Model-Agnostic Explanations X Zhao, W Huang, X Huang, V Robu, D Flynn UAI'21: 37th Conf. on Uncertainty in Artificial Intelligence, 887-896, 2021 | 106 | 2021 |
| A survey of safety and trustworthiness of large language models through the lens of verification and validation X Huang, W Ruan, W Huang, G Jin, Y Dong, C Wu, S Bensalem, R Mu, ... Artificial Intelligence Review 57 (7), 175, 2024 | 83 | 2024 |
| Coverage Guided Testing for Recurrent Neural Networks W Huang, Y Sun, X Zhao, J Sharp, W Ruan, J Meng, X Huang IEEE Transactions on Reliability 71 (3), 1191-1206, 2021 | 68* | 2021 |
| Assessing the Safety and Reliability of Autonomous Vehicles from Road Testing X Zhao, V Robu, D Flynn, K Salako, L Strigini ISSRE'19: IEEE 30th Int. Symp. on Software Reliability Engineering, 13-23, 2019 | 68 | 2019 |
| A Safety Framework for Critical Systems Utilising Deep Neural Networks X Zhao, A Banks, J Sharp, V Robu, D Flynn, M Fisher, X Huang Computer Safety, Reliability, and Security 12234, 244-259, 2020 | 53 | 2020 |
| Probabilistic Model Checking of Robots Deployed in Extreme Environments X Zhao, V Robu, D Flynn, F Dinmohammadi, M Fisher, M Webster AAAI'19: Proc. of the AAAI Conference on Artificial Intelligence 33, 8066-8074, 2019 | 43 | 2019 |
| Assessing safety-critical systems from operational testing: A study on autonomous vehicles X Zhao, K Salako, L Strigini, V Robu, D Flynn Information and Software Technology 128, 106393, 2020 | 41 | 2020 |
| Verifiable self-certifying autonomous systems M Fisher, E Collins, L Dennis, M Luckcuck, M Webster, M Jump, V Page, ... ISSRE'18: IEEE 29th Int. Symp. on Software Reliability Engineering Workshops …, 2018 | 37 | 2018 |
| A New Approach to Assessment of Confidence in Assurance Cases X Zhao, D Zhang, M Lu, F Zeng Computer Safety, Reliability, and Security 7613, 79-91, 2012 | 33 | 2012 |
| Assessing the Reliability of Deep Learning Classifiers Through Robustness Evaluation and Operational Profiles X Zhao, W Huang, A Banks, V Cox, D Flynn, S Schewe, X Huang AISafety'21: Workshop on AI Safety at IJCAI-21, 2021 | 32* | 2021 |
| Reliability Assessment and Safety Arguments for Machine Learning Components in System Assurance Y Dong, W Huang, V Bharti, V Cox, A Banks, S Wang, X Zhao, S Schewe, ... ACM Transactions on Embedded Computing Systems, 2022 | 29* | 2022 |
| SAFARI: Versatile and Efficient Evaluations for Robustness of Interpretability W Huang, X Zhao, G Jin, X Huang ICCV'23: IEEE/CVF Int. Conf. on Computer Vision, 1988-1998, 2023 | 27 | 2023 |
| Position: Building Guardrails for Large Language Models Requires Systematic Design Y Dong, R Mu, G Jin, Y Qi, J Hu, X Zhao, J Meng, W Ruan, X Huang ICML'24: 41st International Conference on Machine Learning, 2024 | 25* | 2024 |
| Modeling the probability of failure on demand (pfd) of a 1-out-of-2 system in which one channel is “quasi-perfect” X Zhao, B Littlewood, A Povyakalo, L Strigini, D Wright Reliability Engineering & System Safety 158, 230-245, 2017 | 24 | 2017 |
| On Reliability Assessment When a Software-based System Is Replaced by a Thought-to-be-Better One B Littlewood, K Salako, L Strigini, X Zhao Reliability Engineering & System Safety 197, 106752, 2020 | 20 | 2020 |
| Interval change-point detection for runtime probabilistic model checking X Zhao, R Calinescu, S Gerasimou, V Robu, D Flynn ASE'20: 35th IEEE/ACM Int. Conf. on Automated Software Engineering, 2020 | 19 | 2020 |
| UAS Operators Safety and Reliability Survey: Emerging Technologies towards the Certification of Autonomous UAS M Osborne, J Lantair, Z Shafiq, X Zhao, V Robu, D Flynn, J Perry ICSRS'19: IEEE Int. Conf. on System Reliability and Safety, 203-212, 2019 | 19 | 2019 |
| Towards integrating formal verification of autonomous robots with battery prognostics and health management X Zhao, M Osborne, J Lantair, V Robu, D Flynn, X Huang, M Fisher, ... SEFM'19: Int. Conf. on Software Engineering and Formal Methods, 105-124, 2019 | 18 | 2019 |
| Conservative claims for the probability of perfection of a software-based system using operational experience of previous similar systems X Zhao, B Littlewood, A Povyakalo, L Strigini, D Wright Reliability Engineering & System Safety 175, 265-282, 2018 | 15 | 2018 |
Xiaowei HuangProfessor of Computer Science, University of LiverpoolVerified email at liverpool.ac.uk
