معرفی
Dr Xiandong Ma is a Reader in Power and Energy Systems at Lancaster University's School of Engineering, where he has been a faculty member since December 2008. His research focuses on intelligent condition monitoring and fault diagnosis of power systems, with particular expertise in wind energy systems and smart grid technologies.
His educational background includes:
- BEng in Electrical Engineering from Jiangsu University (1986)
- MSc in Power Systems and Automation from Nanjing Automation Research Institute (1989)
- PhD in Partial Discharge based High-voltage Plant Condition Monitoring from Glasgow Caledonian University (2002)
Dr Ma's research spans intelligent condition monitoring and fault diagnosis/prognosis of wind power systems and electrical assets, condition-based operations and maintenance of power and energy systems, modeling, optimization, and control of smart/micro grids with renewable energy resources, power conversion and renewable energy integration, and associated machine learning and AI technologies and digital twin solutions. His work bridges theoretical advances with practical engineering applications in the renewable energy sector.
His recent publications demonstrate a strong focus on quantum machine learning applications for wind turbine monitoring, electric vehicle-grid integration challenges, wave energy conversion systems, and nuclear fuel inspection technologies. The research shows a clear trajectory toward more sophisticated AI-driven solutions for energy systems, with increasing emphasis on multi-physics modeling and cross-domain applications.
Dr Ma has received several prestigious recognitions:
- Chartered Engineer
- Fellow of the Institution of Engineering and Technology (FIET)
- Fellow of the Higher Education Academy (FHEA)
- Member of EPSRC Peer Review College
- KTP Fellowship awarded by University of Technology Sydney (2018)
- Ranked in the world's top 2% scientists by Stanford University
He actively supervises numerous PhD students and postdoctoral researchers, with current projects including the Leverhulme Trust-funded "Self-Aware Power Networks: Autonomous Operation at Scale" and several EPSRC-funded initiatives. Dr Ma has secured significant research funding and collaborates extensively with industry partners to translate research into practical applications.
Dr Ma leads research within Lancaster's Energy research group, focusing on the integration of advanced sensing, AI, and control techniques for next-generation power and energy systems. His team works closely with industrial partners including ALSTOM Power and various renewable energy companies to develop innovative solutions for real-world energy challenges.
