Dr Amin Paykani
PhD, FHEA, CEng, MIMechE
Lecturer in Sustainable Propulsion Systems
Research Lead- Centre for Intelligent Transport
Engineering 220, Mile End
| Feedback/ support hours: |
Tuesday 4pm-5pm & Thursday 4pm-5pm (Online) |
| Expertise: | Combustion engineering, Zero/low carbon fuels, low-order modelling, Machine learning, thermal management |
| Research Centre: | Intelligent Transport |
| Affiliations: |
Fellow of The Higher Education Academy (FHEA) Chartered Engineer (IMechE) EPSRC Peer Review College Member UKRI Talent Peer Review College Member |
Brief Biography
Amin Paykani is a Lecturer in Sustainable Propulsion Systems in the School of Engineering and Materials Science (SEMS) at Queen Mary University of London. Prior to joining QMUL, he held academic positions at the University of Hertfordshire and ETH Zurich. Amin's research is primarily focused on studying low/zero-carbon energy vectors for the decarbonisation of transport. He is renowned for his work on the creation of low-order and machine learning-assisted surrogate models, which aim to reduce computational costs in the study of reactive systems. He has been the recipient of several funding grants from EPSRC and Royal Society. He is always looking for high-quality PhD students and postgraduate visitors. If you are interested in any of the topics/areas, please contact me for more details.
* There is an opening for a Chinese Scholarship Council (CSC) scholarship position in my group, focusing on data-driven modelling and optimisation of cooling in raction motors. If you're ready to take your research career to the next level, please send your CV and a cover letter expressing your interest in this exciting opportunity.
Deadline for Applications: 29 January 2025
www.sems.qmul.ac.uk/research/studentships/611/data-driven-optimisation-of-hairpin-winding-and-oil-cooling-in-traction-motors-for-improved-thermal-management
* There is an opening for a Chinese Scholarship Council (CSC) scholarship position in my group, focusing on data-driven modelling and optimisation of cooling in raction motors. If you're ready to take your research career to the next level, please send your CV and a cover letter expressing your interest in this exciting opportunity.
Deadline for Applications: 29 January 2025
www.sems.qmul.ac.uk/research/studentships/611/data-driven-optimisation-of-hairpin-winding-and-oil-cooling-in-traction-motors-for-improved-thermal-management