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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

  • 5 Conference contribution
  • 4 Article

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 journalArticle

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 journalArticle

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 Press

Research output: Chapter in Book/Report/Conference proceedingConference 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 proceedingConference 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 journalArticle

Modeling
Reliability Modeling
Simplification
Demand
Entire