Pablo A. Parrilo

Papers

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About

Pablo A. Parrilo is a pioneering figure in optimization and control theory, whose work bridges rigorous mathematics with transformative applications in robotics and engineering. His research centers on convex optimization, algebraic methods, and hybrid systems, with a focus on developing tractable algorithms for complex, non-convex problems. A major contribution is his groundbreaking work on sum-of-squares (SOS) programming, which has become a cornerstone for verifying stability and safety in nonlinear systems, earning over 10,000 citations. Parrilo’s recent paper, “Towards Tight Convex Relaxations for Contact-Rich Manipulation” (2024), exemplifies his impact: it introduces a novel convex optimization framework for global motion planning in robotic systems with contact interactions, directly addressing the hybrid, discrete-continuous nature of such tasks by reformulating them as shortest-path problems. This work, already cited 11 times, showcases his ability to push boundaries in robotics. A recipient of the IEEE Control Systems Award and a member of the National Academy of Engineering, Parrilo continues to inspire researchers with his elegant, computationally efficient solutions to some of the hardest problems in control and robotics.