Kadhim Hayawi

Papers

Total Citations

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About

Kadhim Hayawi is a researcher at the forefront of intelligent systems and sustainable technology, with a primary focus on electric vehicle (EV) infrastructure and machine learning optimization. His most cited work, "Revolutionizing electric robot charging infrastructure through federated transfer learning and data route optimization" (2025), introduces a novel framework that combines federated learning with data-driven route planning to enhance the efficiency and scalability of autonomous charging networks. This contribution addresses critical challenges in EV adoption—namely, charging station accessibility and energy management—by enabling collaborative, privacy-preserving model training across distributed systems. Although early in its citation impact, the paper’s forward-looking approach signals Hayawi’s role in shaping next-generation smart grid and robotic logistics. His research bridges the gap between theoretical AI advancements and practical infrastructure solutions, offering pathways for reduced operational costs and improved energy distribution. By integrating transfer learning with real-time data optimization, Hayawi’s work holds promise for accelerating the transition to autonomous, eco-friendly transportation systems. As a rising voice in applied AI, he continues to explore how federated architectures can democratize data-driven decision-making in critical infrastructure domains.