معرفی
Dr. Wenjuan Song is a Lecturer in Electrically Powered Aircraft, Propulsion, Electrification & Superconductivity Group at the James Watt School of Engineering, University of Glasgow. She holds a PhD in Electrical Engineering from Beijing Jiaotong University (2019) and has held postdoctoral positions at Victoria University of Wellington (2016–2018) and the University of Bath (2019–2021). Her research focuses on accelerating net-zero transitions in transport sectors through superconductivity and AI-driven solutions.
- Research Interests: Net-zero aviation, renewable energy systems, superconducting fault current limiters, cryogenic systems, and AI applications in electrification.
- Awards: Global Talent (UK Royal Academy of Engineering, 2021), featured in IEEE PES Women in Power, and COST Action publications.
- Teaching: Course coordinator for Simulation of Engineering Systems, Simulation of Aerospace Systems, and Power Engineering 3.
- Professional Activities: Organizing Committee member (UK Fluids Conference 2023), guest editor (Superconductor Science and Technology), and session chair at international conferences.
Her work integrates superconductivity and AI to address challenges in electric aircraft, high-speed rail, and marine electrification. Key contributions include fault detection systems for HTS components and predictive modeling of superconducting materials.
