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About

Christos Kouppas is a robotics researcher specializing in bipedal robot locomotion, balance control, and the application of machine learning and deep reinforcement learning to autonomous robotic systems. His work sits at the intersection of artificial intelligence and physical robotics, with a particular focus on developing energy-efficient and robust controllers capable of operating in real-world, human-collaborative environments. Kouppas is perhaps best known for his contributions to the S.A.R.A.H. (Silent Agile Robust Autonomous Host) project, an Innovate UK-funded initiative that produced a novel bipedal robot employing patent-pending electromagnetic actuators in place of conventional DC motors — a design innovation with significant implications for quiet, efficient locomotion. His 2021 paper on hybrid autonomous controllers combining deep reinforcement learning with pattern generators, his most cited work with 18 citations, addresses the critical challenge of push-recovery in bipedal robots, offering a more adaptive alternative to hard-coded balancing approaches. Earlier work explored extended Normalized Advantage Functions paired with recurrent neural networks to minimize power consumption during balance tasks. Collectively, Kouppas's research demonstrates a sustained commitment to bridging intelligent learning algorithms with practical robotic hardware, making meaningful contributions to the advancement of autonomous humanoid robotics.