People
Faculty
Boris Gutman, Ph.D.
I received my BS in Applied Math and PhD in Biomedical Engineering at UCLA, with postdocs at University College London and USC. During this time (when I wasn’t sailing, running or watching the Golden State Warriors), I developed a few distinct research interests which I have been trying to bring together ever since:
Computational Anatomy & Shape Analysis, or how to measure the shape of human anatomy
Connectomics, or how to quantify the brain’s inter-connectedness
Imaging Genetics, i.e. links between genetics and imaging phenotypes
Machine Learning, especially for modeling diseases of the brain
In 2018, after many years in California, I came to Illinois Tech to start a lab focusing exactly on bringing these things into one coherent mathematical whole. Chicago has been a great backdrop for this. It turns out one can still sail in the Summer here, and besides, there is no ice-boating in California. I do feel a bit conflicted when the Warriors play the Bulls though…
Lab Members
Anvar Kurmukov
Anvar Kurmukov received his BS and MS degrees at Higher School of Economics (HSE, Moscow, Russia), from the department of Computer Science. His research interests include applied machine learning, network science with applications in neuroscience, and computer vision for medical imaging applications. Anvar is also actively contributing to multiple Deep Learning and Computer Vision projects with practical implementations across the Moscow region’s medical centers. Currently, he is a Team Lead at the Artificial Intelligence Research Institute in Moscow, Russia finalizing his Ph.D. Anvar has been first and co-author of papers in Medical Image Analysis, Brain Connectivity, and is an active member of the MICCAI community, both as a reviewer and a contributor.
Yuji Zhao
Yuji Zhao is currently seeking a Ph.D degree at the department of Biomedical Engineering. He received a Master’s degree in Electrical Engineering with specialization in digital signal processing and worked on projects involving convolutional neural networks and CT-dose reduction. Under the supervision of Dr. Boris Gutman, Yuji is developing novel machine learning and pattern recognition techniques in the field of neuroimaging. His research focus is on modeling disease progression and knowledge transfer across neurodegenerative diseases, particularly for predicting the course of Alzheimer’s and Parkinson’s.
Collaborators
ENIGMA Consortium
University of Southern California & WorldwideThe ENIGMA Consortium brings together researchers in imaging genomics to understand brain structure, function, and disease, based on brain imaging and genetic data. We welcome brain researchers, imagers, geneticists, methods developers, and others interested in cracking the neuro-genetic code.