Professor Murphey's research focuses on computational methods in dynamics and control, with applications in neuroscience, health science, robotics, and automation. The group focuses on emergent phenomena in the context of embedded control, biomechanics, and dynamic exploration in engineered and biological systems. The mathematical approaches used by the group lead to many orders of magnitude improvement in computational efficiency for reliable real-time implementation. Applications include assistive exoskeleton control, stabilization of energy networks, bio-inspired active sensing, entertainment robots, robotic exploration, and software-enabled stroke rehabilitation.
See the Projects page.
Ph.D. in Control and Dynamical Systems, California Institute of Technology, 2002
B.S. in Mathematics, University of Arizona, 1997
Professor Murphey has developed the ME 314 Machine Dynamics course, focusing on the application of variational analysis to simulation and design of mechanisms. He has additionally developed ME 454, an introduction to numerical methods in optimal control and a class on active learning in robotics. In 2013 he taught an online version of one of the Engineering Analysis courses as a Coursera Massive Open Online Course (MOOC) (more information can be found at Coursera class Everything is the Same: Modeling Engineered Systems). In all these courses, Professor Murphey focuses on project-based learning. He has been a featured speaker at the National Academy of Engineering Frontiers of Engineering Education Workshop (see his blog here).
See the Publications page.