Papers
1
Total Citations
3
H-Index
1
About
Katie By is a roboticist whose work focuses on the fundamental principles of dynamic locomotion and underactuated systems. Her research explores how robots can achieve efficient, stable movement with minimal actuation, often revealing counterintuitive optimal strategies. Her most cited work, "Nonintuitive Optima for Dynamic Locomotion: The Acrollbot" (2018, 3 citations), introduces a novel two-link planar robot that balances on a single, unactuated wheel—a model she named the acrollbot. By actuating only an internal degree of freedom, By demonstrates how the system can indirectly achieve efficient locomotion, challenging conventional assumptions about robotic control. This work highlights her talent for distilling complex biomechanical and control problems into elegant, mathematically tractable models. Though early in her career, By’s contributions are already shaping how researchers think about energy-efficient, underactuated movement. Her focus on nonintuitive optima offers a fresh perspective for students and engineers designing agile, resource-constrained robots.
Research Focus
Key Achievements
Top Papers
- 1Nonintuitive Optima for Dynamic Locomotion: The Acrollbot3 citations · 2018