Research papers

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". On ArXiv.
• 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. Preprint available.
• 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. Preprint available.
• 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