Faculty Profile

Brad Sutton

Brad Sutton
Brad Sutton
  • Beckman Institute for Advanced Science and Technology
  • Bioengineering
  • Electrical and Computer Engineering
  • Neuroscience
1215D Beckman Institute MC 251
405 N. Mathews
Urbana Illinois 61801
(217) 244-5154


  • Beckman Institute for Advanced Science and Technology
  • Bioengineering
  • Electrical and Computer Engineering
  • Neuroscience

Primary Research Area

  • Bioimaging at Multi-Scale


  • Ph.D., Biomedical Engineering, University of Michigan, 2003


Dr. Sutton joined the Bioengineering Department at the University of Illinois in January, 2006. Dr. Sutton received a B.S. in General Engineering from the University of Illinois at Urbana-Champaign. He earned M.S.￿s in Biomedical and Electrical Engineering and a PhD in Biomedical Engineering from the University of Michigan in 2003. He has affiliations with the Beckman Institute, Electrical and Computer Engineering Department, and the Department of Speech and Hearing Sciences. His research interests are in developing magnetic resonance imaging acquisition, image reconstruction, and systems modeling approaches to understand brain function.

For more information

Teaching Statement

The human body is a complex of non-linear, adaptive systems upon which our lives rest. My objective in teaching is to push students to apply and extend their engineering tools to model, describe, and predict behavior of human physiology while gaining an appreciation for the limits of such models.

Research Statement

My research is focused on developing novel methods to image structure and physiological function with magnetic resonance imaging. Application areas include functional neuroimaging and dynamic imaging of muscle function in speech.

Undergraduate Research Opportunities

During various disease states and even during healthy aging, the human brain undergoes dramatic changes in structural and functional organization, along with changes in metabolic support structures. Magnetic resonance imaging offers many windows into this changing physiology. Analysis of such changes requires applications of linear algebra and statistics upon very large data sets. Currently, there are positions for undergraduates to learn and apply structural analysis methodologies to disease populations such as multiple sclerosis.

Research Interests

  • Neuromuscular coupling
  • Image Reconstruction
  • Magnetic Susceptibility
  • Diffusion Weighted Imaging
  • Dynamic Imaging
  • Functional Magnetic Resonance Imaging

Research Areas

  • Biomedical imaging
  • Diffusion weighted imaging
  • Dynamic imaging
  • Functional MRI
  • Image reconstruction
  • Instrumentation
  • Magnetic susceptibility
  • MRI
  • Neural engineering (general)
  • Neuromuscular coupling
  • Systems modeling approaches to understand brain function

Research Topics

  • Bioimaging at Multi-Scale