Publications

I have produced 50+ publications in top-tier conferences/journals, including:

AI/ML: NeurIPS, ICCV, ECCV, ICML, AAAI, UAI, AAMAS, Springer-ML
Software Engineering : ACM-TOSEM, ACM-TECS, IEEE-TSE, Elsevier-IST, ASE
Safety, Reliability and Security: Elsevier-RESS, IEEE-TR, ISSRE, DSN, CCS, SafeComp
Cyber Physical Systems: Nature-CE, IEEE-RA-L, ICRA, IROS, ITSC, IV

Please refer to my Google Scholar profile for the full list of publications. If you have any problems obtaining these publications, please feel free to contact me.

Featured Publications of Explainable and Trustworthy AI:

[ECCV] ProTIP: Probabilistic Robustness Verification on Text-to-Image Diffusion Models against Stochastic Perturbation.

[ACM TOSEM] Hierarchical Distribution-Aware Testing of Deep Learning.

[ICCV] SAFARI: Versatile and Efficient Evaluations for Robustness of Interpretability.

[UAI] BayLIME: Bayesian Local Interpretable Model-Agnostic Explanations.

[IEEE TR] Coverage Guided Testing for Recurrent Neural Networks.

Featured Publications of Probabilistic Verification of Autonomous Systems

[Nature Comm. Eng. ] Bayesian Learning for the Robust Verification of Autonomous Robots

[ASE] Interval Change-Point Detection for Runtime Probabilistic Model Checking.

[AAAI] Probabilistic Model Checking of Robots Deployed in Extreme Environments.

[IROS] Dependability Analysis of Deep Reinforcement Learning based Robotics and Autonomous Systems through Probabilistic Model Checking.

Featured Publications of Bayesian Reliability Assessment of Safety-Critical Systems

[IEEE TSE] The Unnecessity of Assuming Statistically Independent Tests in Bayesian Software Reliability Assessments.

[Elsevier IST] Assessing Safety-Critical Systems from Operational Testing: A Study on Autonomous Vehicles. (journal extension of the ISSRE'19 work, best paper nominee)

[Elsevier RESS] Modeling the Probability of Failure on Demand (pfd) of a 1-out-of-2 System in Which One Channel is “Quasi-Perfect”.

Featured Publications of Safety Assurance for Learning-Enabled Systems

[ACM TECS] Reliability Assessment and Safety Arguments for Machine Learning Components in System Assurance. (journal extension of the AISafety'21 work, best paper award)

[ITSC] Instance-Level Safety-Aware Fidelity of Synthetic Data and Its Calibration.

[ITSC] STPA for Learning-Enabled Systems: A Survey and a New Practice.

[SafeComp] A Safety Framework for Critical Systems Utilising Deep Neural Networks.

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