Dr Wenjuan Song she/her

Photo of Dr Wenjuan Song
Innovating electrification of energy and transport by intelligent data-driven technology

Assistant Professor/Lecturer in Electrically Powered Aircraft

James Watt School of Engineering
Research interests:
AI, Machine learning, Renewable energy, Electrification, DC link, Propulsion, Protection
Research fields:
Wind farm energy generation and transmission, Electric aircraft powertrain systems, HVDC power grid, Machine learning for protection of magnet, Cryogenic technology and hydrogen generation

Mission Priority Areas

Why do you want to join the DiveIn community?
DiveIn is a new doctoral training initiative, funded by EPSRC under its Strategic Innovation in Doctoral Training scheme, consisting colleagues from across all Schools in the College of Science and Engineering. I am keen to work collaboratively on interdisciplinary research projects aligned with DiveIn’s priority areas. and the priority areas well aligned with my research interest and vision. Exciting to be one supervisor for the CDT community, and empower the next generation of smart electrification of energy and transport.
Personal profile:

Dr. Wenjuan Song (SMIEEE, MIET) is leading the CryoElectric Research Lab and Propulsion, Electrification & Superconductivity Group, in James Watt School of Engineering, University of Glasgow, UK. Dr Song’s research aims to accelerate i) net-zero transition in Transport sector, including aviation, high-speed rail and marine system electrification, and ii) sustainable and highly efficient renewable energy systems using innovative superconducting technology and artificial intelligence techniques.

CDT Fusion magnet project:
This project focuses on advancing high-field superconducting magnets for next-generation fusion reactors. By integrating novel high-temperature superconductors with AI-assisted design and condition monitoring, the project aims to improve magnetic field stability, reduce quench risk, and enable compact, energy-efficient fusion devices. The work supports the global push for clean, virtually limitless energy through practical and scalable fusion technologies.

CDT Electric Aircraft Project:
This project supports the development of all-electric and hybrid-electric aircraft by addressing key challenges in power density, thermal management, and system reliability. Leveraging superconducting machines, lightweight materials, and AI-based control strategies, the project aims to drastically improve propulsion efficiency and reduce emissions in aviation, contributing to the decarbonisation of short- and medium-haul flight.

I am committed to creating an inclusive and supportive environment where all individuals can thrive, regardless of background. I actively promote diversity in my teaching in Simulation courser and Power Engineering, supervision, and research collaborations by adopting inclusive practices, mentoring underrepresented students, and supporting fair recruitment and authorship. I regularly engage with EDI training and contribute to departmental initiatives to ensure equity and belonging are embedded in all aspects of my work.

As a PhD supervisor, I provide clear guidance, strong mentorship, and a supportive environment that empowers students to grow into confident, independent researchers. I encourage open communication, high standards, and a focus on both academic excellence and personal development.

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