Nesrine Ouannes

Papers

Total Citations

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About

Nesrine Ouannes is a researcher in evolutionary robotics and parallel computing, with a focus on developing intelligent, adaptive controllers for autonomous robots. Her work bridges the gap between bio-inspired algorithms and high-performance computing, particularly through the use of CUDA-based architectures to accelerate robot learning and evolution. One of her key contributions is a novel hybrid metaheuristic that combines training and evolution directly within a robot’s onboard system, enabling it to efficiently navigate complex environments—such as walking toward a hidden destination—without external supervision. This approach, detailed in her 2018 paper, demonstrates how parallel processing can dramatically speed up the evolution of robust behaviors. Earlier, in 2011, she explored gait evolution for humanoid robots in physically simulated environments, laying foundational work in adaptive locomotion. Though her citation counts are modest (3 and 2, respectively), her research represents a forward-thinking integration of machine learning, robotics, and GPU-accelerated computation, offering practical pathways for creating more autonomous and responsive robotic systems.