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Dr Arman Eshaghi
1st Floor
Russell Square House
10-12 Russell Square
Dr Arman Eshaghi profile picture
  • Senior Research Fellow
  • Neuroinflammation
  • UCL Queen Square Institute of Neurology
  • Faculty of Brain Sciences

He is currently a National Insitute for Health and Care Research (NIHR) Advanced Fellow at UCL, developing advanced artificial intelligence models using brain imaging and electronic health records. He obtained his medical doctorate degree (M.D) in 2013 from Tehran University of Medical Sciences (the highest ranking medical school in Iran) and has been awarded a PhD in Neuroscience from University College London in 2018. He was awarded the Young Investigator of Year in 2016 by the European Committee for Treatment and Research in Multiple Sclerosis (ECTRIMS). He has been awarded the Jacqueline du PrĂ© Grant in 2011, ECTRIMS-MAGNIMS Fellowship in 2015, and the Multiple Sclerosis International Federation's Ian McDonald Fellowship in 2016. He has previously been working as part of the international network of Progressive MS Alliance working with Prof Olga Ciccarelli, Prof Frederik Barkhof, Prof Alan Thompson, and Dr Declan Chard (London, UK) and led by Prof Douglas Arnold at the McGill University (Canada). He is a member of the Progression of Neurodegenerative Disorders (POND) Team at the Centre for Medical Image Computing at the Department of Computer Science at UCL, working closely with Prof Daniel Alexander. 

His main research interests are the application of model-based machine learning, Bayesian, and causal inference methods to understand the underlying mechanism of progressive multiple sclerosis. 

He serves on the Editorial Board of Neurology, which is the official journal of the American Academy of Neurology. Neurology is the most widely read and one of the most highly cited clinical neurology journals in the world.  

Research Themes
Research Summary
I lead the MS-PINPOINT research group (www.ms-pinpoint.com) that seeks to develop the next-generation of technologies to enable personalized medicine for those living with multiple sclerosis or MS. My research encompasses several aspect of MS using advanced artificial intelligence (AI) from electronic health records (EHRs) to medical images of the brain and spinal cord (MRI). 
Teaching Summary

Supervised five MSc Student, and one PhD student. 

Academic Background
2018   Doctor of Philosophy University College London
2013   Doctor of Medicine Tehran University of Medical Science
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