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About

Hugo T. M. Kussaba is a robotics researcher pushing the boundaries of how elastic and compliant actuation can be harnessed for dynamic, high-performance robot control. His work centers on **bi-stiffness actuation**, **clutched-elastic robots**, and **learning from demonstration**—areas where he bridges the gap between theoretical optimal control and real-time robotic applications. Kussaba’s major contributions include the development of the **Bi-Stiffness Actuation (BSA)** framework, which optimally exploits intrinsic compliance and inertial coupling to enable highly dynamic maneuvers like throwing, and a **fast, predictable braking framework** that ensures safe, real-time control of elastic robots. He has also pioneered **contact-implicit optimal control** for clutched-elastic systems, allowing robots to store and release potential energy with precise timing—a key challenge in the field. With over 15 citations across his most influential papers, his work is gaining traction for its practical impact. Notably, his 2022 BSA paper (6 citations) and his 2023 braking framework (3 citations) are foundational for next-generation elastic robots. Kussaba’s research is shaping how robots learn and execute complex, dynamic tasks safely and efficiently.