Yudu Li

Yudu Li is a Research Assistant Professor in the Department of Bioengineering at the University of Illinois at Urbana-Champaign (UIUC), affiliated with the Beckman Institute and the National Center for Supercomputing Applications. He holds a Ph.D. in Electrical and Computer Engineering from UIUC (2022), an M.S. from the same university (2017), and a B.S. in Electronic Engineering from Tsinghua University (2015).

• Primary Affiliation: Bioengineering Department, College of Engineering
• Secondary Affiliations: Beckman Institute (0%), National Center for Supercomputing Applications (0%)

Research Interests

His research focuses on computational methodologies for biomedical imaging, particularly Magnetic Resonance Imaging (MRI). He develops novel mathematical models and computational frameworks that integrate spin physics, signal modeling, statistical inference, and machine learning to overcome challenges in high-dimensional imaging problems. Key areas include:

• MRI-based metabolic imaging
• Quantitative MRI
• Multimodal neuroimaging
• MRI reconstruction techniques (e.g., SPICE, subspace learning)

Publications & Trends

His work emphasizes high-resolution MRI advancements, particularly in:

• Dynamic metabolic imaging of brain tumors using deuterium MRSI
• Machine learning-driven image reconstruction for faster/safer scans
• Integration of subspace models with deep learning
• Applications in stroke prediction and Alzheimer’s disease

Awards & Honors

• Summa Cum Laude Paper Award (ISMRM, 2023)
• W.S. Moore Award (ISMRM, 2023)
• Young Investigator Award (OCSMRM, 2023)
• Thomas and Margaret Huang Award (UIUC, 2022)

Grants & Labs

Active in collaborative projects at the Beckman Institute, focusing on MRI innovation. His lab develops cutting-edge techniques for brain imaging and metabolic analysis. Notably, he has contributed to fast high-resolution 3D MR spectroscopic imaging and machine learning-enhanced subspace reconstruction methods.