Research papers

2023

• Rees, N., Holding, K., and Sujan, M. "Information governance as a socio-technical process in the development of trustworthy healthcare AI". Preprint available on Arxiv.

2022

• Salako, K., and Zhao, X., "The Unnecessity of Assuming Statistically Independent Tests in Bayesian Software Reliability Assessments" available on Arxix. December 2022.
• Hawkins, R., Picardi, C., Donnell, L., and Ireland, M. "Creating a safety assurance case for an ML satellite-based wildfire detection and alert system". On Arxiv (2022).
• Harbin, J., Gerasimou, S., Matragkas, N., Zolotas, T., Calinescu, R., and Alpizar Santana, M. "Model-driven design space exploration for multi-robot systems in simulation" in Software and Systems Modeling (2022).
• Dong, Y. Huang, W., Bharti, V., Cox, V., Banks, A., Wang, S., Zhao, X, Schewe, S., and Huang, X. "Reliability assessment and safety arguments for machine learning components in system assurance" in ACM Transactions on Embedded Computing Systems (2022). Preprint available.
• Yi Dong, Wei Huang, Vibhav Bharti, Victoria Cox, Alec Banks, Sen Wang, Xingyu Zhao, Sven Schewe, Xiaowei Huang
• Laher, S., Brackstone, C., Reis, S., Nguyen, A., White, S., and Habli, I. "Review of the AMLAS methodology for application in healthcare". The paper is on Arxiv. September 2022.
• Asplund , F., and Ulfvengren, P. "Engineer-centred design factors and methodological approach for maritime autonomy emergency response systems" in Safety (2022). 
• Dong, Y., Zhao, X., and Huang, X. "Dependability analysis of deep reinforcement learning based robotics and autonomous systems through probabilistic model checking" accepted by IROS2022. The paper is on Arxiv.
• Festor, P., Jia, Y., Gordon, A.C., Faisal, A.A., Habli, I., and Komorowski, M. "Assuring the safety of AI-based clinical decision support systems: a case study of the AI Clinician for sepsis treatment" in BMJ Health and Care Informatics (July 2022)
• Sujan, M., White, S., Habli, I., and Reynolds, N. "Stakeholder perceptions of the safety and assurance of artificial intelligence in healthcare" in Safety Science, November 2022
• Zou, J., Dai, X., and McDermid, J.A. "reTSN: Resilient and Efficient Time-Sensitive Network for Automotive In-Vehicle Communication" in IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (July 2022)
• Solène Guenat, et al "Meeting sustainable development goals via robotics and autonomous systems" in Nature Communications, June 2022. AAIP authors include Dr Ana MacIntosh (Programme Manager) and Bilal Kaddouh (Programme Fellow).
• Qi, Y., Ryan Conmy, P., Huang, W., Zhao, X., and Huang, X. "A hierarchical HAZOP-like safety analysis for learning-enabled systems" accepted by the AISafety2022 Workshop at IJCAI2022. Paper available on Arxiv (June 2022).
• Fang, X., Calinescu, R., Paterson, P., and Wilson, J. "PRESTO: Predicting system-level disruptions through parametric model checking". Paper available on Arxiv (May 2022).
• Jia, Y., McDermid, J., Lawton, T., and Habli, I. "The role of explainability in assuring safety of machine learning in healthcare" in IEEE Transactions on Emerging Topics in Computing (May 2022)
• Tahir, Z., and Alexander, R. "Intersection focused situation coverage-based verification and validation framework for autonomous vehicles implemented in CARLA" in International Conference on Modelling and Simulation for Autonomous Systems (April 2022). The complete code and its implementation details are provided in a Github repo.
• Gleirscher, M., Calinescu, R., Douthwaite, J., Lesage, B., Paterson, C., Aitken, J., Alexander, R., and Law, J. "Verified synthesis of optimal safety controllers for human-robot collaboration" in Science of Computer Programming (April 2022).
• Porter, Z., Habli, I., and McDermid, J. "A principle-based ethical assurance argument for AI and autonomous systems" available on Arxiv (March 2022).
• Hodge, V., Hawkins, R., Hilder, J., and Habli, I. "Analysing ultra-wide band positioning for geofencing in a safety assurance context" Open-access on arXiv (March 2022)
• Alasmari, N., Calinescu, R., Paterson, C., and Mirandola, R. "Quantitative verification with adaptive uncertainty reduction" in Journal of Systems and Software (February 2022)
• Calinescu, R., Imrie, C., Mangal, R., Pasareanu, C., Santana, M.A., and Vázquez, G. "Discrete-event controller synthesis for autonomous systems with deep-learning perception components". Available on Arxiv (February 2022).
• Soyer, B., Tettenborn, A., and Leloudas, G. "Remote controlled and autonomous shipping: a UK-based case study" (January 2022)
• Sujan, M., Pool, R., and Salmon, P. "Eight human factors and ergonomics principles for healthcare artificial intelligence" in BMJ Health & Care Informatics (January 2022)

2021

• Hawkins, R. D., Paterson, C., Picardi, C., Jia, Y., Calinescu, R. and Habli, I. "Guidance on the Assurance of Machine Learning in Autonomous Systems (AMLAS)" (February 2021)
• Aftab, H., Gautam, V., Hawkins, R. D., Alexander, R. and Habli, I. "Robust intent classification using bayesian LSTM for clinical conversational agents (CAs)" in EAI MobiHealth November 2021
• Osborne, M., Hawkins, R. D. and Nicholson, M. "An 'as desired' model of the software safety assurance lifecycle" at Safety Critical Systems Symposium (February 2021)
• Habli, I., Alexander, R. and Hawkins, R. D. "Safety cases: an impending crisis?" at Safety Critical Systems Symposium (February 2021)
• Gleirscher, M., Calinescu, R., Douthwaite, J., Lesage, B., Paterson, C., Aitken, J., Alexander, R., and Law, J. "Verified synthesis of optimal safety controllers for human-robot collaboration". Open-access on arXiv (June 2021)
• Sujan, M., and Habli, I. "Safety cases for digital health innovations: can they work?" in BMJ Quality and Safety Journal (May 2021)
• Jia, Y., Lawton, T., McDermid, J.A., Rojas, E. and Habli, I. "A framework for assurance of medication safety using machine learning". Open-access on arXiv (January 2021)
• Vázquez, G., Calinescu, R., and Cámara, J. "Scheduling multi-robot missions with joint tasks and heterogeneous robot teams" at TAROS 2021 (September 2021)
• Weyns, D., Bures, T., Calinescu, R., et al "Six software engineering principles for smarter cyber-physical systems" at SISSY 2021
• Gerasimou, S., Cámara, J., Calinescu, R., Alasmari, N., Alhwikem, F. and Fang, X. "Evolutionary-guided synthesis of verified pareto-optimal MDP policies" at ASE 2021
• Stefanakos, I, Calinescu, R., and Gerasimou, S. "Probabilistic program performance analysis" at SEAA 2021
• Paterson, C., Wu, H., Grese, J., Calinescu, R., Pasareanu, C.S., and Barrett, C. "DeepCert: verification of contextually relevant robustness for neural network image classifiers" at SAFECOMP (September 2021)
• Riley, J., Calinescu, R., Paterson, C., Kudenko, D., and Banks, A. "Utilising assured multi-agent reinforcement learning within safety-critical scenarios" in Procedia Computer Science (2021)
• Sujan, M., Baber, C., Salomon, P., Pool, R., Chozos, N., Aceves-González, C., Cooke, M., Escobar-Galino, C., Flashman, C., Frau, G., Hawkins, R., Hughes, H., Mejia, G., Kaya, G., Kirby, B., Landa-Avila, I.C., Laudanski, K., Lewis, P., Magrabi, F., and White, S. "Human factors and ergonomics in healthcare AI" CIEHF white paper (September 2021)
• Sujan, M. "Muddling through in the intensive care unit – A FRAM analysis of intravenous infusion management" in Resilient Health Care, CRC Press (April 2021)
• Huang, J.C., and Kurniawati, H "An NCAP-like safety indicator for self-driving cars" (April 2021)
• Devitt, S.K., Horne, R., Assaad, Z., Broad, E., Kurniawati, H., Cardier, B., Scott, A., Lazar, S., Gould, M., Adamson, C., Karl, C., Schrever, F., Keay, S., Tranter, K., Shellshear, E., Hunter, D., Brady, M., and Putland, T. "Trust and safety" in Robotics Roadmap for Australia (2021)
• Anderlini, E., Salavasidis, G., Harris, CA., Wu, P., Lorenzo, A., Phillips, AB., and Thomas, G. "A remote anomaly detection system for Slocum underwater gliders" in Ocean Engineering (September 2021)
• Burton, S., McDermid, J.A., Garnett, P., and Weaver, R. "Safety, complexity, and automated driving: holistic perspectives on safety assurance" in Computer (August 2021)
• Burton, S., McDermid, J.A., Garnett, P., and Weaver, R. "Safer complex systems: an initial framework" published by the Royal Academy of Engineering (July 2021)
• Douthwaite, A., Lesage, B., Gleirscher, M., Calinescu, R., Aitken, J.M., Alexander, R., and Law, J. "A modular digital twinning framework for safety assurance of collaborative robotics" in Frontiers in Robotics and AI, December 2021. 
• Wu, P., Harris, C.A., Salavasidis, G., Lorenzo-Lopez, A., Kamarudzaman, I.,  Phillips, A.B., Thomas, G, and Anderlini, E. "Unsupervised anomaly detection for underwater gliders using generative adversarial networks" in Engineering  Applications of Artificial Intelligence Volume 104, September (2021)
• Almohamade, S. S., Clark, J. A., and Law, J. "Mimicry attacks against behavioural-based user authentication for human-robot interaction" at 4th International Workshop on Emerging Technologies for Authorization and Authentication (ETAA), October 2021.
• Gerasimou, S., Camara, J., Calinescu, R., Alasmari, N., Alhwikem, F., and Fang, X. "Evolutionary-Guided Synthesis of Verified Pareto Optimal Policies" in the 36th IEEE/ACM International Conference on Automated Software Engineering (ASE 2021).

• Riley, J., Calinescu, R., Paterson, C., Kudenko, D., and Banks, A. "Reinforcement Learning with Quantitative Verification for Assured Multi-Agent Policies", in 13th International Conference on Agents and Artificial Intelligence, 2021.
• Gleirscher, M., Johnson, N., Karachristou, P., Calinescu, R., Law, J., and Clark, J. "Challenges in the Safety-Security Co-Assurance of Collaborative Industrial Robots", in The 21st Century Industrial Robot: When Tools Become Collaborators pp 191-214 (Springer).
• Festor, P., Luise, G., Komorowski, M., and Faisal, AA. “Enabling risk-aware reinforcement learning for medical interventions through uncertainty decomposition”  in Interpretable Machine Learning in Healthcare (IMLH) at the ICML 2021 Workshop
• Gadd, M., De Martini, D, and Newman, P. “Contrastive learning for unsupervised radar place recognition,” in IEEE International Conference on Advanced Robotics (ICAR), December 2021
• Omeiza, D., Webb, H., Jirotka, M., and Kunze, L. “Explanations in autonomous driving: a survey”, IEEE Transactions on Intelligent Transportation Systems, 2021

• Festor, P., Habli, I., Jia, Y., Gordon, AC., Faisal, AA., and Komorowski, M. “Levels of autonomy and safety assurance for AI-based clinical decision systems”, 4th International Workshop on Artificial Intelligence Safety Engineering (WAISE), September 2021
• Lesage, BMJ-R., and Alexander, R. "SASSI: Safety analysis using simulation-based situation coverage for cobot systems" in proceedings of SafeComp 2021.
• Harbin, J., Gerasimou, S., Matragkas, N., Zolotas, T., and Calinescu, R. "Model-driven simulation-based analysis for multi-robot systems" in ACM/IEEE 24th International Conference on Model Driven Engineering Languages and Systems (MODELS 21).
• Parra, S., Schneider, S., & Hochgeschwender, N. "Specifying QoS requirements and capabilities for component-based robot software" in 2021 IEEE/ACM 3rd International Workshop on Robotics Software Engineering (RoSE) (pp. 29-36). IEEE
• McDermid, J., Jia, Y., Porter, Z., and Habli, I. "Artificial intelligence explainability: the technical and ethical dimensions" in Philosophical Transactions of the Royal Society A, August 2021
• Paterson, C., Calinescu, R., and Picardi, C. "Detection and Mitigation of Rare Subclasses in Deep Neural Network  Classifiers" at AITest 2021
• Păsăreanu, C. "Analysis of neural network takeover-time predictions for shared-control autonomous driving" in VARS '21: Proceedings of the 1st International Workshop on Verification of Autonomous & Robotic Systems, May 2021
  
• Wu, P., Harris, C., Salavasidis, G., Lorenzo-Lopez, A., Kamarudzaman, I.,  Phillips, A., Thomas, G., and Anderlini, E. "Unsupervised anomaly detection for underwater gliders using generative adversarial networks" in Engineering Applications of Artificial Intelligence, Volume 104, September 2021. Github repository linked in the paper.
• Calinescu, R. Alasmari, N., and Gleirscher, M. "Maintaining driver attentiveness in shared-control autonomous driving" presented at 2021 International Symposium on Software Engineering for Adaptive and Self-Managing Systems (SEAMS).
• Khalid, M., Guevara, L., Hanheide, M., Parsons, S. "Assuring autonomy of robots in soft fruit production", 4th UK-RAS Conference for PhD Students & Early-Career Researchers, 2021.
• Guevara, L., Khalid, M., Hanheide, M., and Parsons, S. "Assessing the probability of human injury during UV-C treatment of crops by robots", 4th UK-RAS Conference for PhD Students & Early-Career Researchers, 2021.
• Williams, D., Gadd, M., De Martini, D., and Newman, P. “Fool me once: robust selective segmentation via out-of-distribution detection with contrastive learning” in IEEE International Conference on Robotics and Automation (ICRA), 2021.
• Omeiza, D., Kollnig, K., Web, H., Jirotka, M., and Kunze, L. "Why not explain? Effects of explanations on human perceptions of autonomous driving: a user study". 2021 IEEE International Conference on Advanced Robotics and its Social Impacts (ARSO), 2021
• Omeiza, D., Web, H., Jirotka, M., and Kunze, L. "Towards accountability: providing intelligible explanations in autonomous driving". 2021 IEEE Intelligent Vehicles Symposium (IV), 2021 
• Zhao, X., Huang, W., Banks, A., Cox, V., Flynn, D., Schewe, S., and Huang, X. "Assessing the reliability of deep learning classifiers through robustness evaluation and operational profiles", to be presented at AI Safety 2021. Preprint available.
• Zhao, X., Huang, W., Huang, X., Robu, V., and Flynn, D. "BayLIME: Bayesian Local Interpretable Model-Agnostic Explanations", to be presented at UAI 2021. Preprint available.
• Jia, Y., Kaul, C., Lawton, T., Murray-Smith, R., and Habli, I. "Prediction of weaning from mechanical ventilation using convolutional neural networks" in Artificial Intelligence in Medicine.
• Jia, Y., McDermid, J., and Habli, I "Enhancing the value of counterfactual explanations for deep learning" in AIME 2021: Artificial Intelligence in Medicine in Europe
• Jia, Y., Lawton, T., Burden, J., McDermid, J., and Habli, I. "Safety-Driven Design of Machine Learning for Sepsis Treatment" in Journal of Biomedical Informatics, May 2021.
• Zhao, X., Huang, W., Schewe, S., Dong, Y., and Huang, X. "Detecting Operational Adversarial Examples for Reliable Deep Learning", to be presented at 51st Annual IEEE/IFIP International Conference on Dependable Systems and Networks (DSN2021). Preprint available.
• Ashmore, R., Calinescu, R., and Paterson, C. "Assuring the Machine Learning Lifecycle: Desiderata, Methods, and Challenges" in ACM Computing Surveys, May 2021.
• Fang, X., Calinescu, R., Gerasimou, S., and Alhwikem, F. "Fast Parametric Model Checking through Model Fragmentation". 43rd International Conference on Software Engineering.
• Gleirscher, M., Calinescu, R., and Woodcock, J. "Risk Structures: A Design Algebra for Risk-Aware Machines" in Formal Aspects of Computing, 2021.
• Askarpour, M., Tsigkanos, C., Menghi, C., Calinescu, R., Pelliccione, P., Garcia, S., Caldas, R., von Oertzen, T.J., Wimmer, M., Berardinelli, L., Rossi, M., Bersani, M.M., and Rodrigues, G.S. "RoboMAX: Robotic Mission Adaptation eXemplars". Software Engineering for Adaptive and Self-Managing Systems, 2021. 
• Calinescu, R., Alasmari, N., and Gleirscher, M. "Maintaining driver attentiveness in shared-control autonomous driving". Software Engineering for Adaptive and Self-Managing Systems, 2021.
• Pakdamanian, E., Sheng, S., Baee, S., Heo, S., Kraus, S., Feng, L. "DeepTake: Prediction of Driver Takeover Behavior using Multimodal Data" accepted for publication at the ACM Conference on Human Factors in Computing Systems (CHI) 2021
• Grese, J.M., Pasareanu, C., Pakdamanian, E. "Formal Analysis of a Neural Network Predictor in Shared-Control Autonomous Driving" presented at AIAA Scitech 2021 Forum.

2020

• Chang, W., Burton, S., Lin, C-W., Zhu, Q. "Intelligent and Connected Cyber-Physical Systems: A Perspective from Connected Autonomous Vehicles". In book Intelligent Internet of Things: From Device to Fog and Cloud, January 2020.

• Burton, S. McDermid, J. Garnett, P. Weaver, R. "An Initial Framework Assessing the Safety of Complex Systems". In CCS2020 - Conference on Complex System 2020.

• Ward, F.R., and Habli, I. "An Assurance Case Pattern for the Interpretability of Machine Learning in Safety-Critical Systems". In ​Third International Workshop on Artificial Intelligence Safety Engineering.

• Birch, J., Blackburn, D., Botham, J., Habli, I. "A Structured Argument for Assuring Safety of the Intended Functionality (SOTIF). In Computer Safety, Reliability, and Security, SAFECOMP 2020 Workshops.

• Calinescu, R., Mirandola, R., Perez-Palacin, D., Weyns, D. "Understanding Uncertainty in Self-adaptive Systems". In 1st IEEE International Conference on Autonomic Computing and Self-Organizing Systems.

• Gautam, V., Gheraibia, Y., Alexander, R. "Runtime Decision Making Under Uncertainty in Autonomous Vehicles". Proceedings of the Workshop on Artificial Intelligence Safety (SafeAI 2021), February 2020.

• Picardi, C., Paterson, C., Hawkins, R., Calinescu, R., Habli, I. "Assurance Argument Patterns and Processes for Machine Learning in Safety-Related Systems". Proceedings of the Workshop on Artificial Intelligence Safety (SafeAI 2020), February 2020.

• Sujan, M., Furniss, D., Hawkins, R., and Habli, I. "Human Factors of Using Artificial Intelligence in Healthcare: Challenges That Stretch Across Industries". Safety-Critical Systems Symposium, February 2020.

• Jaradat, O., Sljivo, I, Hawkins, R., and Habli, I. "Modular Safety Cases for the Assurance of Industry 4.0". Safety-Critical Systems Symposium, February 2020.
• Gleirscher, M. "Yap: Tool Support for Deriving Safety Controllers from Hazard Analysis and Risk Assessments" in Luckuck, M. & Farrell, M. (Eds.), Formal Methods for Autonomous Systems (FMAS), 2nd Workshop, Electronic Proceedings in Theoretical Computer Science, 329, 31-47. Open Publishing Association, 2020.
• De Martini, D., Gadd, M., and Newman, P. "kRadar++: Coarse-to-Fine FMCW Scanning Radar Localisation", in Sensors, Special Issue on Sensing Applications in Robotics, vol. 20, no. 21, p. 6002, 2020. Multidisciplinary Digital Publishing Institute (MDPI), October 2020
• Zhao, X., Calinescu, R., Gerasimou, S., Robu, V., and Flynn, D. "Interval Change-Point Detection for Runtime Probabilistic Model Checking", in 35th IEEE/ACM International Conference on Automated Software Engineering (ASE ’20), September 2020 (virtual event).
• Gleirscher, M. and Calinescu, R. "Safety controller synthesis for collaborative robots" in Engineering of Complex Computer Systems, 25th International Conference, 28 - 31 October 2020, Singapore, 2020.
• Foster, S., Gleirscher, M. and Calinescu, R. "Towards deductive verification of control algorithms for autonomous marine vehicles" in Engineering of Complex Computer Systems, 25th International Conference, Singapore, 2020.
• Habli, I., Alexander, R., Hawkins, R., Sujan, M., McDermid, J., Picardi, C., and Lawton, T. "Enhancing COVID-19 decision making by creating an assurance case for epidemiological models", in BMJ Health and Care Informatics, September 2020.
• Mario Glerscher, M., Johnson, N., Karachristou, P., Calinescu, R., Law, J., and Clark, J. "Challenges in the Safety-Security Co-Assurance of Collaborative Industrial Robots". Book chapter in The 21st Century Industrial Robot -- When Tools become Collaborators, University of York, 2020.
• Foster, S., Gleirscher, M., and Calinescu, R. "Towards Deductive Verification of Control Algorithms for Autonomous Marine Vehicles", preprint of a paper accepted for presentation at the 25th International Conference on Engineering of Complex Computer Systems (ICECCS 2020).
• Gleirscher, M. and Calinescu, R. "Safety Controller Synthesis for Collaborative Robots", preprint of a paper accepted for presentation at the 25th International Conference on Engineering of Complex Computer Systems (ICECCS 2020).
• McDermid, J., and Jia, Y. "Safety of Artificial Intelligence: A Collaborative Model", in proceedings of the Workshop on Artificial Intelligence Safety 2020.
• Monkhouse, H., Habli, I., and McDermid, J. "An Enhanced Vehicle Control Model for Highly Automated Driving Safety", in Reliability Engineering and System Safety, 5 Jun 2020
• Jia, Y., Burden, J., Lawton, T., and Habli, I. "Safe Reinforcement Learning for Sepsis Treatment", in 8th IEEE International Conference on Healthcare Informatics, 30 Nov 2020
• Gauerhof, L., Hawkins, R., Picardi, C., Paterson, C., Hagiwara, Y., and Habli, I. "Assuring the Safety of Machine Learning for Pedestrian Detection at Crossings", in SAFECOMP 2020 (39th International Conference on Computer Safety, Reliability and Security), September  2020
• Hodge, J., Hawkins, R., and Alexander, R. "Deep reinforcement learning for drone navigation using sensor data", in Neural Computing and Applications (2020)
• Zhao, X., Banks, A., Sharp, J., Robu, V., Flynn, D., Fisher, M., and Huang, X. A Safety Framework for Critical Systems Utilising Deep Neural Networks, a preprint accepted by SafeComp 2020.
• Gadd, M., De Martini, D., Marchegiani, L., Newman, P., Kunze, L. “Sense-Assess-eXplain (SAX): Building Trust in Autonomous Vehicles in Challenging Real-World Driving Scenarios,” in Proceedings of the IEEE Intelligent Vehicles Symposium (IV), Workshop on Ensuring and Validating Safety for Automated Vehicles (EVSAV), (Las Vegas, NV, USA), October 2020
• Williams, D., De Martini, D., Gadd, M., Marchegiani, L., and Newman, P. “Keep off the Grass: Permissible Driving Routes from Radar with Weak Audio Supervision,” in IEEE Intelligent Transportation SystemsConference (ITSC), (Rhodes, Greece), September 2020
• Furniss, D., Nelson, D., Habli, I., White, S., Elliott, M. Reynolds, N., and Sujan, M. "Using FRAM to explore sources of performance variability in intravenous infusion administration in ICU: A non-normative approach to systems contradictions" Elsevier Applied Ergonomics, July 2020
• Kaul, P., De Martini, D., Gadd, M., Newman, P. “RSS-Net: Weakly-Supervised Multi-Class Semantic Segmentation with FMCW Radar,” in Proceedings of the IEEE Intelligent Vehicles Symposium (IV), June 2020
• Gadd, M., De Martini, D., Newman, P. “Look Around You: Sequence-based Radar Place Recognition with Learned Rotational Invariance” in IEEE/ION Position, Location and Navigation Symposium (PLANS), April 2020
• Habli, I., Lawton, T., and Porter, Z. Artificial intelligence in health care: accountability and safety, in the Bulletin of the World Health Organization, April 2020
• Picardi, C., Paterson, C., Hawkins, R., Calinescu, R., and Habli, I. Assurance Argument Patterns and Processes for Machine Learning in Safety-Related Systems, in proceedings of the Workshop on Artificial Intelligence Safety (SafeAI 2020)
• Barnes, D., Gadd, M., Murcutt, P., Newman, P., and Posner, I. The Oxford Radar RobotCar Dataset: A Radar Extension to the Oxford RobotCar Dataset, in Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), 2020.
• Saftescu, S., Gadd, M., De Martini, D., Barnes, D., and Newman, P. Kidnapped Radar: Topological Radar Localisation using Rotationally-Invariant Metric Learning, in Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), 2020.
• Tang, TY., De Martini, D., Barnes, D., and Newman, P. RSL-Net: Localising in Satellite Images From a Radar on the Ground, in IEEE Robotics and Automation Letters (RA-L) 2020
• Sujan, M., Furniss, D., Hawkins, R., Habli, I. Human Factors of Using Artificial Intelligence in Healthcare: Challenges That Stretch Across Industries, in proceedings of the Safety-Critical Systems Symposium, February 2020.

2019

• Menon, C., and Alexander, R. A safety-case approach to the ethics of autonomous vehicles. Safety and Reliability Society Journal, December 2019
• Sujan, M., Furniss, D., Grundy, K., Grundy, H., Nelson, D., Elliott, M., White, S., Habli, I., and Reynolds, N. Human factors challenges for the safe use of AI in patient care. BMJ Health and Care Informatics, 2019
• Magrabi, F., Habli, I., Sujan, M., Wong, D., Thimbleby, H., Baker, M., and Coiera, E. "Why is it so difficult to govern mobile apps in healthcare?". BMJ Health and Care Informatics, November 2019.
• Burton, S., Habli, I., Lawton, T., McDermid, J., Morgan, P., and Porter, Z. Mind the gaps: Assuring the safety of autonomous systems from an engineering, ethical, and legal perspective. Artificial Intelligence Journal February 2020
• Bloomfield, R., Khlaaf, H., Ryan Conmy, P., and Fletcher, G. Disruptive innovations and disruptive assurance: assuring machine learning and autonomy in Computer, vol. 52, no. 09, pp. 82-89, 2019. doi: 10.1109/MC.2019.2914775 September 2019
• Sujan, M., Furniss, D., Embrey, D., Elliott, M., Nelson, D., White, S., Habli, I., and Reynolds, N. Critical Barriers to Safety Assurance and Regulation of Autonomous Medical Systems, presented at ESREL September 2019
• Kinoshita, S., Kinoshita, Y., and Takeyama, M. A modelling approach for system life cycles assurance presented at ASSURE workshop as part of SAFECOMP September 2019
• Burton, S., Gauerhof, L., Hawkins, RD., Habli, I., and Sethy , B. Confidence Arguments for Evidence of Performance in Machine Learning for Highly Automated Driving Functions, presented at Safecomp 2019 (WAISE workshop).
• Wei, R., Kelly, T., Dai, X., Zhao, S., and Hawkins, R. Model based system assurance using the structured assurance case metamodel. August 2019
• Gheraibia, Y., Kabir, S., Aslansefat, K., Sorokos, I., and Papadopoulos, Y. Safety + AI: A Novel Approach to Update Safety Models using Artificial Intelligence.
• Picardi, C., Hawkins, RD., Paterson, C., and Habli, I. A Pattern for Arguing the Assurance of Machine Learning in Medical Diagnosis Systems, presented at Safecomp 2019.
• McDermid, JA. Jia, Y., Habli, I. Towards a Framework for Safety Assurance of Autonomous Systems, August 2019.
• Habli, I., Jia, Y., White, S., Gabriel, G., Lawton, T., Sujan, M., Tomsett, C. Development and piloting of a software tool to facilitate proactive hazard and risk analysis of Health Informatics Technology, June 2019
• Habli, I., Jia, Y., Lawton, T., White, SP. Developing a Safety Case for Electronic Prescribing.
• Picardi, C., and Habli, I. Perspectives on Assurance Case Development for Retinal Disease Diagnosis Using Deep Learning. May 2019
• Calinescu, R., Camara, J., and Paterson, C. Socio-Cyber-Physical Systems: Models, Opportunities, Open Challenges. 5th International Workshop on Software Engineering for Smart Cyber-Physical Systems, May 2019.
• Ashmore, R., Calinescu, R., and Paterson, C. Assuring the Machine Learning Lifecycle: Desiderata, Methods, and Challenges, May 2019 arXiv preprint.
• Paterson, C., Calinescu, R., Wang, D., and Manandhar, SK. Using Unstructured Data to Improve the Continuous Planning of Critical Processes Involving Humans.
• Bennaceur, A., Ghezzi, C., Tei, K., Kehrer, T., Weyns, D., Calinescu, R., Dustdar, S., Hu, Z., Honiden, S., Ishikawa, F., et al. Modelling and Analysing Resilient Cyber-Physical Systems. HAL preprint, April 2019.
• Calinescu, R., Paterson, C., and Johnson, K. Efficient Parametric Model Checking Using Domain Knowledge. IEEE Transactions on Software Engineering, April 201
• Weyns, D., Bencomo, N., Calinescu, R., Cámara, J., Ghezzi, C., Grassi, V., Grunske, L., Inverardi, P., Jézéquel, J-M., Malek, S., Mirandola, R., Mori, M., and Tamburrelli, G. Perpetual Assurances for Self-Adaptive Systems.
• Menon, C., Holthaus, P. Does a loss of social credibility impact robot safety?, in Proceedings of the 9th International Conference on Performance, Safety and Robustness in Complex Systems, pp. 18 – 25, 2019) was awarded a Best Paper award at PESARO19

2018

• Calinescu, R., Paterson, C., and Johnson, K. Efficient Parametric Model Checking Using Domain Knowledge. arXiv paper, December 2018.
• Ellison, M., Calinescu, R., Paige, RF. Evaluating cloud database migration options using workload models. Journal of Cloud Computing 7(1):6
• Habli, I., White, S., Sujan, M., Harrison, S., and Ugarte, M. What is the safety case for health IT? A study of assurance practices in England. Safety Science, 110, 324-335
• Ashjaei, M., Clegg, K., Corneo, L., Hawkins, R., Jaradat, O., Gulisano, V.M. and Nikolakopoulos, Y. Service Level Agreements for Safe and Configurable Production Environments. In 2018 IEEE 23rd International Conference on Emerging Technologies and Factory Automation (ETFA) (Vol. 1, pp. 1252-1255)
• Bragg, J., and Habli, I. What is Acceptably Safe for Reinforcement Learning? First International Workshop on Artificial Intelligence Safety Engineering
• Porter, Z., Habli, I., Monkhouse, H., and Bragg, J. The Moral Responsibility Gap and the Increasing Autonomy of Systems, First International Workshop on Artificial Intelligence Safety Engineering
• Paterson, C., and Calinescu, R. Observation-Enhanced QoS Analysis of Component-Based Systems. IEEE Transactions on Software Engineering (Early Access)
• Pedro, D., Habli, I., Gregory, S., Alexander, R., Clark, J., and Medina-Bulo, I. Evaluation of Mutation Testing in a Nuclear Industry Case Study. IEEE Transactions on Reliability 99 (2018): 1-14
• Calinescu, RC, and Yonbawi, SR. Towards a Hierarchical-Control Architecture for Distributed Autonomous Systems. FLoC Workshop on Verification and Validation of Autonomous System
• Calinescu, R., Češka, M., Gerasimou, S., Kwiatkowska, M., and Paoletti, N. Efficient synthesis of robust models for stochastic systems. Journal of Systems and Software 143:140-158
• Calinescu, R., Johnson, K., and Paterson, C. Efficient parametric model checking using domain-specific modelling patterns. 40th International Conference on Software Engineering: New Ideas and Emerging Results, pp. 61-64
• Gerasimou, S., Calinescu, R., and Tamburrelli, G. Synthesis of probabilistic models for quality-of-service software engineering. Automated Software Engineering Journal 30:1-47
• Habli, I., and White, S. Hazard and Risk Analysis for Health Informatics: Fundamental Challenges and New Directions, Safety Critical Systems Symposium
• McDermid, JA., Daffey, K. Safety of Artificial Intelligence and its role in Autonomy: A Maritime Perspective, presented at Safety Critical Systems Symposium.
• De Oliveira, AL., Braga, RT V., Masiero, PC., Papadopoulos, Y., Habli, I. and Kelly, TP. Variability Management in Safety-Critical Software Product Line Engineering, 2018 International Conference on Software Reuse

2017

• Calinescu, R., Weyns, D., Gerasimou, S., Iftikhar, MU., Habli, I., and Kelly, T. ENTRUST: Engineering Trustworthy Self-Adaptive Software with Dynamic Assurance Cases. IEEE/ACM 40th International Conference on Software Engineering (ICSE):495
• Mason, G., Calinescu, R., Kudenko, D., and Banks, A. Assurance in reinforcement learning using quantitative verification. Advances in Hybridization of Intelligent Methods, pp. 71-96, Springer