Research Output per year
Personal profile
Research interests
- Probabilistic verification of autonomous systems.
- Exploring the limits of what can be claimed rigorously for system reliability.
- Modelling of software design diversity for fault tolerance.
Biography
Xingyu Zhao received his BEng in Software Engineering and MSc in Control Science and Engineering from Beihang University, Beijing. He joined the Centre for Software Reliability (CSR), City, University of London as a PhD student in September 2013 and obtained a Doctor degree in Computer Science in November 2016. He then worked as a Post-doc Research Associate at CSR, where he was actively involved in the research projects DIverse Software Project (DISPO) and Diversity and Defence in Depth for Security - A Probabilistic Approach (D3S). Since May, 2018, he joined the Smart System Group at Heriot-Watt University and doing research on developing practical self-certification methods for robot and autonomous systems. In 2019, he is also a Programme Fellow of the Assuring Autonomy International Programme at the University of York.
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- 1 Similar Profiles
Robots
Engineering & Materials Science
Model checking
Engineering & Materials Science
Condition monitoring
Engineering & Materials Science
Bayesian networks
Engineering & Materials Science
Software design
Engineering & Materials Science
Fault tolerance
Engineering & Materials Science
Automotive industry
Engineering & Materials Science
Wind turbines
Engineering & Materials Science
Co Author Network
Recent external collaboration on country level. Dive into details by clicking on the dots.
Research Output 2011 2019
Assessing the Safety and Reliability of Autonomous Vehicles from Road Testing
Zhao, X., Robu, V., Flynn, D., Salako, K. & Strigini, L., 20 Jul 2019, (Accepted/In press) The 30th International Symposium on Software Reliability Engineering.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
Machine learning methods for wind turbine condition monitoring: A review
Stetco, A., Dinmohammadi, F., Zhao, X., Robu, V., Flynn, D., Barnes, M., Keane, J. & Nenadic, G., Apr 2019, In : Renewable Energy. 133, p. 620-635 16 p.Research output: Contribution to journal › Article
Open Access
File
Condition monitoring
Wind turbines
Learning systems
Feature extraction
Decision trees
Probabilistic Model Checking of Robots Deployed in Extreme Environments
Zhao, X., Robu, V., Flynn, D., Dinmohammadi, F., Fisher, M. & Webster, M., 17 Jul 2019, Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence. AAAI Press, p. 8066-8074 9 p. (Proceedings of the AAAI Conference on Artificial Intelligence; vol. 33, no. 1).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
Open Access
File
Model checking
Robots
Statistical Models
Towards Integrating Formal Verification of Autonomous Robots with Battery Prognostics and Health Management
Zhao, X., Osborne, M., Lantair, J., Robu, V., Flynn, D., Huang, X., Fisher, M., Papacchini, F. & Ferrando, A., 2019, Software Engineering and Formal Methods: SEFM 2019. Ölveczky, P. C. & Salaün, G. (eds.). Springer, p. 105-124 20 p. (Lecture Notes in Computer Science; vol. 11724).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
Open Access
File
Health
Robots
Liquid fuels
Model checking
Unmanned aerial vehicles (UAV)
UAS Operators Safety and Reliability Survey: Emerging Technologies Towards the Certification of Autonomous UAS
Osborne, M., Lantair, J., Shafiq, Z., Zhao, X., Robu, V., Flynn, D. & Perry, J., 4 Sep 2019, (Accepted/In press) 4th International Conference on System Reliability and Safety.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
Prizes
Best Paper Award Finalist, The 30th International Symposium on Software Reliability Engineering (ISSRE 2019)
Xingyu Zhao (Recipient), Valentin Robu (Recipient), David Flynn (Recipient), Kizito Salako (Recipient) & Lorenzo Strigini (Recipient), 28 Oct 2019
Prize: Prize (including medals and awards)
Software reliability
Testing