Faculty Directory
Todd Murphey

Charles Deering McCormick Professor in Teaching Excellence

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 data-driven control, information theory in physical systems, and embodied intelligence.  Example projects include robotic exploration using electrosense, robotic exploration using mechanical contact, human-in-the-loop control, and shared control for rehabilitation/assistive devices.  

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


    A. Mavrommati, E. Tzorakoleftherakis, I. Abraham, and T. D. Murphey, “Real-time area coverage and target localization using receding-horizon ergodic exploration,” IEEE Transactions on Robotics, vol. 34, no. 1, 2018.

    A. Ansari and T. D. Murphey, “Sequential Action Control: Closed-form optimal control for nonlinear and hybrid systems,” IEEE Transactions on Robotics, vol. 32, no. 5, pp. 1196–1214, 2016.

    A. Mavrommati, J. Schultz, and T. D. Murphey, “Real-time mode scheduling using single-integration hybrid optimization for linear time-varying systems,” IEEE Transactions on Automation Science and Engineering, vol. 13, no. 3, pp. 1385–1398, 2016.

    E. Tzorakoleftherakis, T. D. Murphey, and R. A. Scheidt, “Augmenting sensorimotor control using goal-aware vibrotactile stimulation during reaching and manipulation behaviors,” Experimental Brain Research, vol. 234, no. 8, pp. 2403–2414, 2016.

    A. Ansari and T. D. Murphey, “Minimum sensitivity control for planning with parametric and hybrid uncertainty,” International Journal of Robotics Research, vol. 35, no. 7, pp. 823–839, 2016.

    E. Tzorakoleftherakis, A. Ansari, A. Wilson, J. Schultz, and T. D. Murphey, “Model-based reactive control for hybrid and high-dimensional robotic systems,” IEEE Robotics and Automation Letters, vol. 1, no. 1, pp. 431–438, 2016.

    T. Caldwell and T. D. Murphey, “Sufficient descent and backtracking for optimal mode scheduling,” Nonlinear Analysis: Hybrid Systems, vol. 21, pp. 59–83, 2016.

    L. Miller, Y. Silverman, M. A. MacIver, and T. Murphey, “Ergodic exploration of distributed information,” IEEE Transactions on Robotics, vol. 32, no. 1, pp. 36–52, 2016.


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.