Associate Professor of Mechanical Engineering
2145 Sheridan Road
Evanston, IL 60208-3109
Ph.D. Control and Dynamical Systems, California Institute of Technology, Pasadena, CA
B.S. Mathematics (summa cum laude), University of Arizona, Tucson, AZ
Modeling and control of complex mechanical and biological systems
- 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
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.
L. M. Miller and T. D. Murphey, “Trajectory optimization for continuous ergodic exploration,” in American Controls Conf. (ACC), 2013.
D. Pekarek and T. D. Murphey, “A projected Lagrange-d’Alembert principle for forced nonsmooth mechanics and optimal control,” in IEEE Int. Conf. on Decision and Control (CDC), 2013.
Y. P. Leong and T. D. Murphey, “Feature localization using kinematics and impulsive hybrid optimization,” IEEE Transactions on Automation Science and Engineering, vol. 10, no. 4, pp. 957 – 968, 2013.
T. Caldwell and T. D. Murphey, “Single integration optimization of linear time-varying switched systems,” IEEE Transactions on Automatic Control, vol. 57, no. 6, pp. 1592–1597, 2012.
Y. Silverman, L. Miller, M. MacIver, and T. D. Murphey, “Optimal planning for information acquisition,” in IEEE Int. Conf. on Intelligent Robots and Systems (IROS), 2013.
A. D. Wilson and T. D. Murphey, “Optimal trajectory design for well-conditioned parameter estimation,” in IEEE Int. Conf. on Automation Science and Engineering (CASE), 2013.