Muhammad Saleem Khan

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About

Muhammad Saleem Khan is a researcher at the forefront of cloud robotics and intelligent systems, with a focus on developing adaptive task planning frameworks that bridge artificial intelligence and robotic autonomy. His most cited work, "Intelligent task planner for cloud robotics using level of attention empowered with fuzzy system" (2020), introduces a novel approach that integrates fuzzy logic with attention-based mechanisms to optimize task allocation in cloud-connected robotic environments. This contribution addresses critical challenges in real-time decision-making, enabling robots to prioritize tasks dynamically based on contextual awareness—a key step toward more responsive and efficient autonomous systems. With over 5 citations, this paper has garnered attention for its practical implications in industrial automation and smart environments. Khan’s research underscores the synergy between cloud computing and robotics, offering scalable solutions for complex, multi-agent scenarios. His work is particularly valuable for students and researchers exploring the intersection of fuzzy systems, attention modeling, and distributed robotics, providing a foundation for future innovations in intelligent task scheduling and human-robot collaboration.