Biography
Bio
I studied telecom engineering at the University of Seville (Spain),
and then moved to Stockholm (Sweden) for a second M.Sc. degree in
electrical engineering at the Royal Institute of Technology (KTH), where
I also completed a master's program in wireless systems with a Ernst
Johnson fellowship. I got involved in medical applications for the first
time during my M.Sc. thesis work at the Karolinska Institute, also in
Stockholm. After two research assistantships at the University of
Seville and the University of Copenhagen (Denmark), I carried out my
doctoral studies in biomedical engineering at the University of
California, Los Angeles (UCLA, in USA) with a Fulbright Science &
Technology grant. After my Ph.D., I was a postdoctoral fellow for two
and a half years at the Martinos Center for Biomedical Imaging in Boston
(USA), and a Marie Curie fellow for two years at the Basque Center on
Cognition, Brain and Language in San Sebastian (Spain). I joined University College London (UCL) in
May 2016 with a Starting Grant of the European Research Council (ERC)
with the title: "Building Next-Generation Computational Tools for High
Resolution Neuroimaging Studies". I split my time between UCL and the Laboratory of Computational Neuroimaging at the Martinos Center, directed by Prof. Bruce Fischl. I am also a research affiliate at the Massachusetts Institute of Technology.
Research
My research has recently been focused on building high resolution models of human brain anatomy with ex vivo imaging data. Using brains from cadavers, we can acquire MRI data for a long time, which yields images with very high resolution. We can also perform histological slicing and analysis of the images, which yields excellent contrast between brain structures. Ex vivo MRI and histology can be combined to build very accurate models of brain anatomy, which can in turn be applied to automatically analyze in vivo MRI scans at high resolution for a wide range of neuroimaging studies.
Publications, code, blog, and more
This can all be found in my website at: http://www.jeiglesias.com
Recent Publications
- Iglesias JE. A ready-to-use machine learning tool for symmetric multi-modality registration of brain MRI. Sci Rep. 2023 04 24. 13(1):6657
- Chavva IR, Crawford AL, Mazurek MH, Yuen MM, Prabhat AM, Payabvash S, Sze G, Falcone GJ, Matouk CC, de Havenon A, Kim JA, Sharma R, Schiff SJ, Rosen MS, Kalpathy-Cramer J, Iglesias Gonzalez JE, Kimberly WT, Sheth KN. Deep Learning Applications for Acute Stroke Management. Ann Neurol. 2022 10. 92(4):574-587