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About

Reza Ghorbani is a robotics researcher whose work spans bipedal locomotion, energy-efficient walking mechanisms, and autonomous robotic systems. His most significant contributions lie in the biomechanics of humanoid robots, particularly in developing innovative approaches to reduce energy consumption during bipedal walking. Ghorbani's pioneering research on adjustable stiffness artificial tendons — especially applied to the ankle joint — has offered promising solutions to one of the field's central challenges: minimizing energy dissipation caused by impact forces during leg transitions. His neural network-based stabilization approach for bipedal standing, optimized through genetic algorithms, earned 35 citations and remains his most influential work, demonstrating the power of combining machine learning with classical control theory. Ghorbani's investigations into semi-passive dynamic walking and controllable joint stiffness have informed the development of humanoid platforms such as WABIAN-2R, advancing realistic human locomotion simulation. Early in his career, he also contributed to multi-robot coordination through the ARVAND middle-sized soccer robot project within the RoboCup framework, addressing teamwork strategies and goalkeeper behavior in competitive autonomous systems. Collectively, his body of work reflects a consistent focus on making robotic locomotion more biologically plausible, mechanically efficient, and practically deployable — contributions that continue to inform researchers working at the intersection of biomechanics and robotics engineering.