Maegan Tucker

Maegan Tucker is an Assistant Professor in the Department of Electrical and Computer Engineering at the Georgia Institute of Technology, starting her position in January 2024. She teaches ECE 4560: Introduction to Robotics and Automation and maintains an active research program focused on robotics and control systems.

Dr. Tucker's research centers around achieving stable and user-preferred locomotion using formal methods from nonlinear control theory and machine learning, with specific applications toward robotic assistive devices. Her work bridges the gap between theoretical control methods and practical applications in human-robot interaction, particularly in the domain of exoskeletons and prosthetics. She employs techniques from hybrid zero dynamics, barrier functions, and preference-based learning to develop robust locomotion controllers that can be customized to individual users' needs and preferences.

Her recent publications reveal a strong focus on integrating formal control theory with user-centered approaches, particularly in the development of exoskeletons and assistive devices. The trend in her work shows a progression from theoretical control methods toward increasingly human-centered applications, with a growing emphasis on preference-based learning techniques that allow for personalized device tuning. Her research spans multiple disciplines including robotics, control theory, machine learning, and biomechanics, with a consistent thread of ensuring safety and robustness in human-robot interaction.

Dr. Tucker has developed the POLAR (Preference Optimization and Learning Algorithms for Robotics) Toolbox, which supports her research in preference-based learning for robotics applications. Her GitHub profile shows active development of tools and repositories related to robotics research, particularly focused on locomotion control and human-robot interaction.