Research Output per year
Personal profile
Research interests
- Exploring the limits of what can be claimed rigorously for system reliability.
- Assessment of "possible perfection" with respect to software faults.
- Probabilistic model checking for robotic systems.
- 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.
Fingerprint Fingerprint is based on mining the text of the person's scientific documents to create an index of weighted terms, which defines the key subjects of each individual researcher.
Condition monitoring
Engineering & Materials Science
Model checking
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
Contractors
Engineering & Materials Science
Co Author Network
Recent external collaboration on country level. Dive into details by clicking on the dots.
Research Output 2011 2019
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
Conservative claims for the probability of perfection of a software-based system using operational experience of previous similar systems
Zhao, X., Littlewood, B., Povyakalo, A., Strigini, L. & Wright, D., Jul 2018, In : Reliability Engineering and System Safety. 175, p. 265-282 18 p.Research output: Contribution to journal › Article
Open Access
File
Software engineering
Probabilistic Model Checking of Robots Deployed in Extreme Environments
Zhao, X., Robu, V., Flynn, D., Dinmohammadi, F., Fisher, M. & Webster, M., 1 Nov 2018, (Accepted/In press) Thirty-Third AAAI Conference on Artificial Intelligence (AAAI-2019). AAAI PressResearch output: Chapter in Book/Report/Conference proceeding › Conference contribution
Open Access
File
Verifiable self-certifying autonomous systems
Fisher, M., Collins, E. C., Dennis, L. A., Luckcuck, M., Webster, M., Jump, M., Page, V., Patchett, C., Dinmohammadi, F., Flynn, D., Robu, V. & Zhao, X., 19 Nov 2018, 2018 IEEE International Symposium on Software Reliability Engineering Workshops (ISSREW). IEEE, p. 341-348 8 p.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
Open Access
File
Automotive industry
Aviation
Modeling the probability of failure on demand (pfd) of a 1-out-of-2 system in which one channel is “quasi-perfect”
Zhao, X., Littlewood, B., Povyakalo, A., Strigini, L. & Wright, D., Feb 2017, In : Reliability Engineering and System Safety. 158, p. 230-245 16 p.Research output: Contribution to journal › Article
Modeling
Reliability Modeling
Simplification
Demand
Entire