Official Job Title
Assistant Professor
Email Address
Office Building
Office Room Number

Maegan received her PhD in Mechanical Engineering (ME) from the California Institute of Technology (Caltech) in May 2023. Prior, she also received a M.S. in ME from Caltech in 2019 and a B.S. in ME from Georgia Tech in 2017. After graduating with her PhD, Maegan conducted a brief postdoc at Caltech (May - August 2023), followed by a brief research position at Disney Research (September - December 2023). Generally speaking, her research interests lie at the intersection of control theory and human-robot interaction, with specific applications towards lower-limb assistive devices. Much of her research is centered around the question: “What is the right way to walk?”. In her free time, Maegan enjoys puzzles, playing video games, and the piano.

  • Lower-Body Assistive Devices
  • Bipedal Locomotion
  • Nonlinear Control Theory
  • Human-Robot Interaction
  • Preference-Based Learning
  • Human Biomechanics
Distinctions & Awards
  • Dean’s Jr. Professorship
  • Caltech Centennial Prize for the Best Thesis in Mechanical and Civil Engineering award (2023)
  • Caltech Simoudis Discovery Prize (2022)
  • Berkeley ME Rising Star (2020)
  • ICRA 2020 Best Overall Paper (Awarded)
  • ICRA 2020 Best Paper in Human-Robot Interaction (Awarded)
  • NSF Graduate Research Fellow (2019-2022)
  • Tucker, M.*, Novoseller, E.*, et al. "Preference-Based Learning for Exoskeleton Gait Optimization." In 2020 IEEE International Conference on Robotics and Automation (ICRA), 2020. (*Denotes equal contribution) []
  • Tucker, M., Csomay-Shanklin, N., Ma, W., & Ames, A. D. "Preference-based learning for user-guided HZD gait generation on bipedal walking robots." In 2021 IEEE International Conference on Robotics and Automation (ICRA), 2021. []
  • Tucker, M., Csomay-Shanklin, N., and Ames, A. D. “Robust Bipedal Locomotion: Leveraging Saltation Matrices for Gait Optimization.” In 2023 IEEE International Conference on Robotics and Automation (ICRA), 2023. []
  • Tucker, M., and Ames, A. D. “An input-to-state stability perspective on robust locomotion.” IEEE Control Systems Letters. 2023. []