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Photo of Sulzer, James

james.sulzer@austin.utexas.edu
Office Location: ETC 4.146D

James Sulzer

Assistant Professor

Department Research Areas:
Biomechanical and Biomedicine Engineering

Department Research Areas:
Robotics and Intelligent Mechanical Systems

https://sites.utexas.edu/rewire

An assistant professor in Mechanical Engineering since Fall 2013, Dr. Sulzer obtained his Ph.D. in Mechanical Engineering at Northwestern University and the Rehabilitation Institute of Chicago in 2009, investigating exoskeletal assistance for people following stroke. He then went on to the Swiss Federal Institute of Technology, Zurich (ETHZ) for four years of postdoctoral research, investigating novel modes of neurotherapy using real time functional magnetic resonance imaging (rtfMRI).

The research in Dr. Sulzer's lab is motivated by the large gaps of knowledge that are preventing full recovery of patients following stroke. His current research focuses on two main topics: 1) finding the minimum amount of assistance, if any, that will restore healthy gait in people after stroke and 2) development of novel, neurally-based rehabilitation strategies. Dr. Sulzer's approach starts by identifying the problem from neuroscientific, biomechanics and clinical perspectives, and then pursuing appropriate and eventually, translatable solutions. This highly multi-disciplinary research has necessitated the formation of strong domestic and international collaborations with clinicians, neuroscientists, kinesiologists, physicists and engineers.

Dr. Sulzer has been awarded the ETH Fellowship as well as predoctoral awards from the American Heart Association and the Department of Veterans Affairs. He founded and organized the first international conference on rtfMRI neurofeedback in 2012. He also co-founded the first university-wide business plan competition, research fair, and the interdisciplinary medical device design course at Northwestern known as NUvention.

Key interests:
  • Robotic exoskeletons
  • Biomechanics
  • Neuroscience
  • Stroke rehabilitation
  • Real time fMRI
  • Sensorimotor learning and control