Maegan Tucker

Maegan Tucker is an Assistant Professor at Georgia Institute of Technology with joint appointments in the School of Electrical and Computer Engineering and the Woodruff School of Mechanical Engineering. Her research focuses on achieving dynamic robotic bipedal locomotion using nonlinear control theory and machine learning, particularly for assistive devices. She earned a B.S. in Mechanical Engineering from Georgia Tech (2017), M.S. and Ph.D. from Caltech (2019, 2023), followed by postdoctoral and research positions at Caltech and Disney Research. Her work emphasizes human-robot interaction, robust control, and preference-based learning for exoskeleton customization. Key awards include the Caltech Centennial Prize and NSF Graduate Research Fellowship.

Education:

• Bachelor of Science in Mechanical Engineering, Georgia Tech (2017)
• Master of Science in Mechanical Engineering, Caltech (2019)
• Ph.D. in Mechanical Engineering, Caltech (2023)

Research Interests:

• Control theory applied to human-robot interaction
• Nonlinear control for bipedal locomotion
• Preference-based learning for exoskeleton gait optimization
• Development of assistive lower-limb devices

Recent work explores the intersection of formal control methods and user preferences to achieve stable, natural robotic locomotion. Her publications highlight advancements in gait synthesis, robustness, and human-centered design.

Awards:

• Dean’s Jr. Professorship
• Caltech Centennial Prize (2023)
• Caltech Simoudis Discovery Prize (2022)
• NSF Graduate Research Fellowship (2019-2022)

Her lab focuses on interdisciplinary robotics, blending mechanical engineering, control theory, and machine learning to create assistive technologies that prioritize user comfort and safety. Current projects include developing algorithms for real-time gait adaptation and enhancing exoskeleton personalization through Bayesian optimization.