Staff Profile

Biography

Dr. Zepeng Liu is a lecturer in Electrification at Newcastle University since 2023. He received the B.Eng. degree in Electrical Engineering and Electronics from the University of Liverpool, Liverpool, U.K., in 2015, the M.S. degree in Power Systems Engineering from University College London, London, U.K., in 2016, and the Ph.D. degree in Electrical and Electronic Engineering from the University of Manchester, Manchester, U.K, in 2021. From 2021 to 2023, he was a Research Associate with the Department of Automatic Control and Systems Engineering, University of Sheffield, Sheffield, U.K.

Dr. Zepeng Liu awarded the Chinese Government Award for Outstanding Self-financed Students Abroad in 2021. Only 500 PhD students receive this Award per year all over the world. He has published numbers of high quality journals including IEEE Trans Industr Electron, IEEE Trans Industr Inform, IEEE Trans Instrum Meas, IEEE Trans Syst Man Cybern, etc. His research interests include complex system modelling, system identification, frequency analysis, time-frequency representation, sparse representation and nonlinear filtering, and data-driven analysis. The application areas include condition monitoring and fault diagnosis for wind turbine components and systems, digital manufacturing, and structural health monitoring.

Languages

English, Chinese

Links

Google Scholar: Click here.

ResearchGate: Click here.

LinkedIn: Click here.

Last updated: 11 Dec 2023

Dr Liu is a member of the Electrical Power research group and his research publications and profile can be viewed on Google Scholar, and ResearchGate.

Opportunities

Dr Liu is looking for enthusiastic and highly motivated candidates to conduct PhD research. If you are interested in the areas listed in the Research Interests below, please feel free to contact zepeng.liu@newcastle.ac.uk for discussions.

Research Interests

Modelling and analysis for complex systems: 

· Condition monitoring and fault detection

· Non-Destructive Testing

· Structural Health Monitoring

· Cyber-physical systems

· Digital manufacturing

· Smart structures and systems

System theory and frequency analysis: 

· Data-driven-based digital twin 

· Nonlinear system modelling and analysis in the frequency domain

· Machine and statistical learning, Neural networks

· Sparse representation and nonlinear filtering

Smart devices

· Hardware and software design