Miguel Rosa Morales
m.rosa-morales.1@research.gla.ac.uk
Research title: Superconductivity in Applied Field Magnetoplasmadynamic Thrusters for Aerospace Propulsion Applications
Research summary
Biography
I completed my undergraduate degree at the University of Puerto Rico in 2020, graduating with a Bachelor of Science in Mechanical Engineering, focused on combat robotics and manufacturing. I followed up with an MEng in Engineering Management from the Polytechnic University of Puerto Rico in 2023 to further develop my management skills. MSc in Robotics and AI from the University of Glasgow (2023) to expand my knowledge in the ML&AI field. Currently pursuing a PhD in Aerospace Engineering, exploring the intersection of electrical propulsion and AI for space applications.
Current Research
My current research involves the use of artificial intelligence and superconducting technology for electrical propulsion in space applications.
Research Group
Member of the Propulsion, Electrification and Superconductivity group.
Publications
2026
Bai, Yuechen, Russo, Giacomo, Song, Wenjuan 
ORCID: https://orcid.org/0000-0001-8003-7038, Rosa Morales, Miguel, Fabbri, Massimo, Marzocchi, Tommaso, Minucci, Simone, Morandi, Antonio and Yazdani-Asrami, Mohammad ORCID: https://orcid.org/0000-0002-7691-3485
(2026)
Intelligent design optimisation of an HTS Flux pump for a superconducting magnet in applied field-magnetoplasmadynamic thruster.
IEEE Transactions on Applied Superconductivity,
(Accepted for Publication)
Rosa-Morales, Miguel, Ravichandran, Matthew, Song, Wenjuan ORCID: https://orcid.org/0000-0001-8003-7038 and Yazdani-Asrami, Mohammad ORCID: https://orcid.org/0000-0002-7691-3485
(2026)
Physically interpretable and AI-powered applied-field thrust modelling for magnetoplasmadynamic space thrusters using symbolic regression: towards more explainable predictions.
Aerospace, 13(3),
245.
(doi: 10.3390/aerospace13030245)
Articles
Bai, Yuechen, Russo, Giacomo, Song, Wenjuan ORCID: https://orcid.org/0000-0001-8003-7038, Rosa Morales, Miguel, Fabbri, Massimo, Marzocchi, Tommaso, Minucci, Simone, Morandi, Antonio and Yazdani-Asrami, Mohammad ORCID: https://orcid.org/0000-0002-7691-3485
(2026)
Intelligent design optimisation of an HTS Flux pump for a superconducting magnet in applied field-magnetoplasmadynamic thruster.
IEEE Transactions on Applied Superconductivity,
(Accepted for Publication)
Rosa-Morales, Miguel, Ravichandran, Matthew, Song, Wenjuan ORCID: https://orcid.org/0000-0001-8003-7038 and Yazdani-Asrami, Mohammad ORCID: https://orcid.org/0000-0002-7691-3485
(2026)
Physically interpretable and AI-powered applied-field thrust modelling for magnetoplasmadynamic space thrusters using symbolic regression: towards more explainable predictions.
Aerospace, 13(3),
245.
(doi: 10.3390/aerospace13030245)