Shokoufeh Golshani completed her undergraduate studies double majoring in Biomedical and Electrical Engineering at the Amirkabir University of Technology (AUT), Iran. She subsequently continued her studies in Advanced Medical Imaging Research Lab (AMIR Lab) at the same institute and received her Master’s degree in biomedical Engineering in 2014. Her research focus was on improving the speed and quality of strain imaging through cardiovascular magnetic resonance polar tagging. The outstanding results were published in 5 international conference papers and one MRM journal paper. Her abstract entitled “Efficient Radial Tagging: Undersampled Radial Acquisition with Polar Fourier Transform Reconstruction” was awarded the ISMRM Magna Cum Laude Merit Award. In collaboration with her supervisor, Dr. Abbas Nasiraei Moghaddam, she have published a US patent application. During her master, she also gained precious teaching experience through instructing the Electric Circuit & Measurement Laboratory and Electronic Circuits Laboratory courses (undergraduate courses) and working as a teacher assistant in Cardiovascular Biomechanics course (graduate course) in consecutive semesters.

Currently, she has been awarded a Marie Curie Early Stage Researcher scholarship in the BQ-Minded project, an international research project on quantitative magnetic resonance imaging funded by the European Union’s Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement. She joined the Centre for Computational Imaging and Simulation Technologies in Biomedicine (CISTIB) at the University of Leeds, UK, as a research assistant in 2019. She has begun her Ph.D. studies jointly in the school of computing and the school of medicine under the supervision of Prof. Alejandro Frangi and Prof. Jurgen Schneider. The main aim of her current project is to accelerate diffusion MRI measurements using state-of-the-art hardware- and software-based methodologies.

Research Interests

MRI, Sequence Development, Medical Imaging, Image-based Modeling, Real-time imaging & reconstruction, Cardiovascular MRI, Parallel Imaging and processing, Compressed sensing, diffusion MRI.

Link to publications on google scholar:

https://scholar.google.co.uk/citations?hl=en&user=BcrIIgkAAAAJ