Noel Csomay-Shanklin
California Institute of Technology, Georgia Institute of Technology
Papers
17
Total Citations
240
H-Index
9
About
Noel Csomay-Shanklin is a robotics researcher whose work spans legged locomotion, motion planning, and model-based control, with particular emphasis on bridging theoretical guarantees and real-world robustness. His research has made significant contributions to dynamic walking and hopping robots, developing frameworks that address the fundamental challenges of underactuation, model uncertainty, and safety in complex environments. His most-cited work on Branch Model Predictive Control (72 citations) introduced an elegant approach to interactive multi-modal motion planning that explicitly accounts for the unpredictable reactive behaviors of uncontrolled agents. In legged locomotion, Csomay-Shanklin has advanced online learning methods to compensate for model inaccuracies during real-time control (52 citations), enabling more reliable deployment on physical hardware. His contributions extend to coupled control systems and Control Lyapunov Functions for quadrupedal locomotion, offering formal stability guarantees for interconnected robotic systems. Notably, his work on episodic learning combined with Control Barrier Functions addresses safety under imperfect model knowledge, a critical concern for real hardware deployment. With over 200 cumulative citations across his published work, Csomay-Shanklin has established himself as an emerging force in the field of provably safe, dynamically capable autonomous robots.
Research Focus
Key Achievements
Top Papers
- 1Interactive Multi-Modal Motion Planning With Branch Model Predictive Control72 citations · 2022
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