Yudu Li, Ph.D
Postdoctoral Research Associate
Beckman Institute | University of Illinois Champaign-Urbana
Title: AI-powered brain mapping using magnetic resonance
Abstract: Understanding the brain —how it works and what goes wrong when it is injured or diseased — is considered one of the last frontiers in science and has posed significant challenges for scientists and engineers to develop effective tools to meet this objective. Magnetic resonance is a fundamental property of elementary particles. The discovery of magnetic resonance and its wide-ranging applications have been recognized by five Nobel Prizes. And yet, magnetic resonance has never ceased to amaze those in the field with new capabilities being developed every few years. This talk will discuss a new technique known as SPICEx (SPectroscopic Imaging by exploiting spatiospectral CorrElation) for brain mapping. SPICEx uses a subspace mathematical framework to effectively integrate rapid scanning, sparse sampling, constrained image reconstruction, quantum simulation, and machine learning. Preliminary results show an unprecedented capability to enable simultaneous mapping of brain tissue properties and metabolism using intrinsic magnetic resonance signals from multiple molecules. In this talk, I’ll will give an overview of SPICEx and also show some “SPICY” brain imaging experimental results we have obtained to demonstrate its unique capability and potential.
Bio: Yudu Li is a Postdoctoral Research Associate with the Computational Imaging Group at the Beckman Institute at University of Illinois Urbana-Champaign (UIUC). He obtained his Ph.D. and M.S. degrees advised by Prof. Zhi-Pei Liang at UIUC and B.Eng. at Tsinghua University. Yudu’s research mainly focuses on developing computational methodologies for biomedical imaging, with the emphasis on magnetic resonance imaging (MRI) and magnetic resonance spectroscopic imaging (MRSI). His research has been recognized by a number of awards, including the Young Investigator Award (1st Place) from the Overseas Chinese Society for Magnetic Resonance in Medicine (OCSMRM), Thomas and Margaret Huang Award for Graduate Research, Mavis Future Faculty Fellowship, the Rambus Computer Engineering Fellowship, and the Yee Fellowship Award.
