Uljad Berdica

University of Oxford, New York University

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About

Uljad Berdica is a researcher at the forefront of intelligent robotics, specializing in the intersection of soft robotics, reinforcement learning, and advanced manufacturing. His primary contributions lie in developing learning-based control strategies for highly deformable systems, addressing the fundamental challenge of modeling and controlling robots with nonlinear, compliant dynamics. In his highly cited 2024 work, Berdica pioneered the use of reinforcement learning controllers for soft robotic manipulators, leveraging learned environments to overcome the limitations of traditional analytical methods. This approach enables more robust and adaptive control without relying on oversimplified assumptions. Additionally, his 2021 research on mobile 3D printing robot simulation introduced a novel framework that integrates mobile robot platforms with physics-based simulations of viscoelastic fluids, tackling the complex, time-variant interactions between printing materials and robotic systems. Through these contributions, Berdica is advancing the practical deployment of soft robots and autonomous manufacturing, demonstrating how learning-based methods can unlock new capabilities in unstructured environments.