- Phone: (941) 487-4522
- Email: email@example.com
- Office Location: HNS 207
- Mail Location: HNS E172C
B.S., Computer Engineering, Tufts University
Interests: Biologically Informed Robotics, Computational Physiology, Embedded Systems
Professor Eaton became fascinated by the role of morphology in control while developing her graduate dissertation on biologically informed robotic control algorithms. During a postdoctoral research fellowship in muscle physiology at the University of California, Irvine, she came to appreciate that robots can be used to support the study of animal life, just as animal physiology can support the design of more capable robotic systems. Professor Eaton loves collaborating with biologists to design robots and physics-based simulations as testbeds for physiological hypotheses, and uses principles of animal physiology to design more agile, energy efficient robots. When computer scientists and biologists collaborate, everybody wins!
- Machine Learning for Visual Thinkers
- Robot Modeling & Control
- Embedded Systems
- Intermediate Python: Simulation & Game Design
- Computer Architecture
- Exploring structural control of stiffness in synthetic tendon. CE Eaton, T Ramdhoni**, and RS Karp**. CLAWAR 2019: 22nd International Conference on Climbing and Walking Robots and the Support Technologies for Mobile Machines (CLAWAR). August, 2019.
- Compliant substrates disrupt elastic energy storage in jumping tree frogs. CM Reynaga, CE Eaton, GA Strong**, E Azizi. Integrative and Comparative Biology 59 (6), 1535-1545. December, 2019.
- Resistance to radial expansion limits muscle strain and work. E Azizi, AR Deslauriers, NC Holt, CE Eaton. Biomechanics and modeling in mechanobiology 16 (5), 1633-1643. April, 2017.
- Periodic spring–mass running over uneven terrain through feedforward control of landing conditions. LR Palmer III, CE Eaton. Bioinspiration & biomimetics 9 (3), 036018. August, 2014.