| 2026 | ICSE | Structural Causal World Models: Towards An Assurance Framework for Safety-Critical Systems and Safeguarded AI. | Jie Zou, Simon Burton, Radu Calinescu, Ioannis Stefanakos, Roger Rivett |
| 2026 | SAC | Structural Causal World Models for Safety Assurance of AI-based Autonomy. | Jie Zou, Ioannis Stefanakos, Sepeedeh Shahbeigi Roudposhti, Simon Burton, Radu Calinescu, Kester Clegg, Roger Rivett |
| 2025 | EDCC | Insights from Railway Professionals: Rethinking Railway Assumptions Regarding Safety and Autonomy. | Josh Hunter, John A. McDermid, Simon Burton |
| 2025 | ISSRE | A Case Study on Defining Traceable Machine Learning Safety Requirements for an Automotive Perception Component. | Sepeedeh Shahbeigi, Richard Hawkins, Simon Burton, Victoria J. Hodge, Colin Paterson, Ibrahim Habli |
| 2025 | SMC | Formal Safety and Robustness Verification of Nonlinear Vehicle Systems Under Uncertainty Using Sum-of-Squares Optimization. | Jannis Erz, Simon Burton, Eric Sax |
| 2024 | ISoLA | Emergence in Multi-agent Systems: A Safety Perspective. | Philipp Altmann, Julian Schnberger, Steffen Illium, Maximilian Zorn, Fabian Ritz, Tom Haider, Simon Burton, Thomas Gabor |
| 2024 | SAC | Can you trust your Agent? The Effect of Out-of-Distribution Detection on the Safety of Reinforcement Learning Systems. | Tom Haider, Karsten Roscher, Benjamin Herd, Felippe Schmoeller Roza, Simon Burton |
| 2024 | SAC | Can you trust your ML metrics? Using Subjective Logic to determine the true contribution of ML metrics for safety. | Benjamin Herd, Simon Burton |
| 2024 | SAFECOMP | Uncertainty-Aware Evaluation of Quantitative ML Safety Requirements. | Simon Burton, Benjamin Herd, Joo-Vitor Zacchi |
| 2024 | SAFECOMP | A Deductive Approach to Safety Assurance: Formalising Safety Contracts with Subjective Logic. | Benjamin Herd, Joo-Vitor Zacchi, Simon Burton |
| 2023 | AAAI | Safety Assurance with Ensemble-based Uncertainty Estimation and overlapping alternative Predictions in Reinforcement Learning. | Dirk Eilers, Simon Burton, Felippe Schmoeller da Roza, Karsten Roscher |
| 2023 | ICLR | Statistical Property Testing for Generative Models. | Emmanouil Seferis, Simon Burton, Chih-Hong Cheng |
| 2023 | ICLR | Can Conformal Prediction Obtain Meaningful Safety Guarantees for ML Models? | Emmanouil Seferis, Simon Burton, Chih-Hong Cheng |
| 2023 | PRDC | Safeguarding Learning-based Control for Smart Energy Systems with Sampling Specifications. | Chih-Hong Cheng, Venkatesh Prasad Venkataramanan, Pragya Kirti Gupta, Yun-Fei Hsu, Simon Burton |
| 2022 | ISSRE | Safety Assessment: From Black-Box to White-Box. | Iwo Kurzidem, Adam Misik, Philipp Schleiss, Simon Burton |
| 2022 | PRDC | Automating Safety Argument Change Impact Analysis for Machine Learning Components. | Carmen Crlan, Lydia Gauerhof, Barbara Gallina, Simon Burton |
| 2022 | SAFECOMP | Logically Sound Arguments for the Effectiveness of ML Safety Measures. | Chih-Hong Cheng, Tobias Schuster, Simon Burton |
| 2022 | SAFECOMP | Formally Compensating Performance Limitations for Imprecise 2D Object Detection. | Tobias Schuster, Emmanouil Seferis, Simon Burton, Chih-Hong Cheng |
| 2021 | DAC | Invited: Hardware/Software Co-Synthesis and Co-Optimization for Autonomous Systems. | Wanli Chang, Shuai Zhao, Simon Burton, Haitong Wang, Ting Chen, Nan Chen, Neil C. Audsley |
| 2021 | EDCC | Dynamic Risk Management for Safely Automating Connected Driving Maneuvers. | Marta Grobelna, Joo-Vitor Zacchi, Philipp Schlei, Simon Burton |
| 2021 | SAFECOMP | Safety Assurance of Machine Learning for Chassis Control Functions. | Simon Burton, Iwo Kurzidem, Adrian Schwaiger, Philipp Schleiss, Michael Unterreiner, Torben Grber, Philipp Becker |
| 2019 | SAFECOMP | Confidence Arguments for Evidence of Performance in Machine Learning for Highly Automated Driving Functions. | Simon Burton, Lydia Gauerhof, Bibhuti Bhusan Sethy, Ibrahim Habli, Richard Hawkins |
| 2018 | DAC | Semi-automatic safety analysis and optimization. | Peter Munk, Andreas Abele, Eike Thaden, Arne Nordmann, Rakshith Amarnath, Markus Schweizer, Simon Burton |
| 2018 | SAFECOMP | Structuring Validation Targets of a Machine Learning Function Applied to Automated Driving. | Lydia Gauerhof, Peter Munk, Simon Burton |
| 2018 | SAFECOMP | Challenges in Assuring Highly Complex, High Volume Safety-Critical Software. | John MacGregor, Simon Burton |
| 2017 | SAFECOMP | Making the Case for Safety of Machine Learning in Highly Automated Driving. | Simon Burton, Lydia Gauerhof, Christian Heinzemann |
| 2016 | ISSRE | Dependability Challenges in the Model-Driven Engineering of Automotive Systems. | Rakshith Amarnath, Peter Munk, Eike Thaden, Arne Nordmann, Simon Burton |
| 2001 | PROFES | A Family-Oriented Software Development Process for Engine Controllers. | Karen Allenby, Simon Burton, Darren Lee Buttle, John A. McDermid, John Murdoch, Alan Stephenson, Mike Bardill, Stuart Hutchesson |
| 1998 | ICFEM | Towards Industrially Applicable Formal Methods: Three Small Steps and One Giant Leap. | John A. McDermid, Andy Galloway, Simon Burton, John A. Clark, Ian Toyn, Nigel J. Tracey, Samuel H. Valentine |