Brad Sutton
Brad Sutton he/him/his
Professor, Bioengineering
(217) 244-5154
1215C Beckman Institute

For More Information


  • 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 Neuroscience Program. His research interests are in developing magnetic resonance imaging acquisition, image reconstruction, and systems modeling approaches to understand brain function.

Academic Positions

  • Adjunct Professor, Department of Clinical Veterinary Medicine, College of Veterinary Medicine, UIUC, 6/2023-present
  • Health Innovation Professor, Carle Illinois College of Medicine, 8/2022 - 7/2027
  • Affiliate, National Center for Supercomputing Applications (NCSA), 8/2022-present

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, including changes with disease and aging. 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

Research Topics

Chapters in Books

Selected Articles in Journals

Articles in Conference Proceedings

Professional Societies

  • ASEE Member since 2019
  • AIMBE Member since 2017

Service to Federal and State Government

  • NIH ad hoc review panels, 2018-2021.

Other Outside Service

  • External Advisory Board, MR Research Facility, University of Iowa. 2020-present.

Recent Courses Taught

  • BIOE 302 - Modeling Human Physiology
  • BIOE 420 - Intro Bio Control Systems
  • BIOE 497 BS (BIOE 497 BS2) - Individual Study
  • BIOE 572 - Biological Measurement II