Faculty Directory
Todd Murphey

Charles Deering McCormick Professor in Teaching Excellence

Associate Professor of Mechanical Engineering


2145 Sheridan Road
Tech B286
Evanston, IL 60208-3109

847-467-1041Email Todd Murphey


Neuroscience and Robotics Lab (NxR)


Mechanical Engineering


Master of Science in Robotics Program

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Ph.D. Control and Dynamical Systems, California Institute of Technology, Pasadena, CA

B.S. Mathematics (summa cum laude), University of Arizona, Tucson, AZ

Research Interests

Professor Murphey's research focuses on computational methods in dynamics and control.  The group focuses on computational models of embedded control, biomechanical simulation, dynamic exploration, and hybrid control.  Much of the work uses structured integration (numerical techniques specifically suited to mechanical systems) to ensure stability and robustness of the numerical technique.  Example projects include simulation and control synthesis for a biomechanical model of the human hand, real-time control of robotic systems using structured integration, stabilization of large-scale power network models using a single bit of control authority, mechanical simulation of rat whiskers, numerical modeling of contact in locomotion, and dynamic search for underwater vehicles using electrosense for localization and mapping.   His group's work on robotic marionettes has been featured at the Museum of Science and Industry, Chicago.

Significant Recognition

  • National Science Foundation CAREER award (2006)
  • Defense Science Study Group 2014-2015

Significant Professional Service

  • Associate Editor for IEEE Transactions on Automation Science and Engineering
  • Editor for IEEE Transactions on Robotics

Selected Publications

    L. Miller, Y. Silverman, M. A. MacIver, and T. Murphey, “Ergodic exploration of distributed information,” IEEE Transactions on Robotics, In Press.


    A. Ansari and T. D. Murphey, “Minimum sensitivity control for planning with parametric and hybrid uncertainty,” International Journal of Robotics Research, In Press.


    D. Pekarek and T. D. Murphey, “Discrete Lagrangian mechanics for nonsmooth nonseparable systems,” International Journal for Numerical Methods in Engineering, In Press.


    E. Johnson, J. Schultz, and T. D. Murphey, “Linearizations of variational integrators for analysis and optimization,” IEEE Transactions on Automation Science and Engineering, vol. 12, no. 1, pp. 14–152, 2015.


    A. Wilson, J. Schultz, and T. D. Murphey, “Trajectory synthesis for Fisher information maximization,” IEEE Transactions on Robotics, vol. 30, no. 6, pp. 1358–1370, 2014.


    B. Quist, V. Seghete, L. Huet, T. D. Murphey, and M. J. Z. Hartmann, “Modeling forces and moments at the base of a rat vibrissa during non contact whisking and whisking against an object,” Journal of Neuroscience, vol. 34, pp. 9828–9844, July 2014.


    V. Seghete and T. D. Murphey, “Uniqueness conditions for simultaneous impact in locomotion: existence, uniqueness, and design consequences,” IEEE Transactions on Automation Science and Engineering, vol. 11, no. 1, pp. 154–168, 2014.


    L. Miller and T. D. Murphey, “Simultaneous optimal estimation of mode transition times and parameters applied to simple traction models,” IEEE Transactions on Robotics, vol. 29, no. 6, pp. 1496–1503, 2013.


In the Classroom

Professor Murphey developed the Coursera Massive Open Online Course (MOOC) "Everything Is the Same: Modeling Engineered Systems" and had over 18,000 students enroll in Autumn, 2013. The course was based on one of the core undergraduate classes in systems analysis (EA3), a class he has innovated through development of classroom experiments. Moreover, he 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. In all these courses, Professor Murphey focuses on project-based learning.