Ali Muhammad Shaikh

University of Science and Technology of China

Papers

Total Citations

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About

Ali Muhammad Shaikh is a leading researcher at the intersection of artificial intelligence and robotics, with a primary focus on bio-inspired neural networks and autonomous navigation. His most-cited work, "DSQN: Robust path planning of mobile robot based on deep spiking Q-network" (2025), has already garnered 23 citations, showcasing his innovative integration of spiking neural networks with reinforcement learning for real-world robotic control. Shaikh’s major contribution lies in developing energy-efficient, brain-inspired algorithms that enable mobile robots to navigate complex, dynamic environments with enhanced robustness and adaptability—a critical step toward practical autonomous systems. Beyond this flagship paper, his research spans deep learning, neuromorphic computing, and multi-agent coordination, often emphasizing computational efficiency without sacrificing performance. Shaikh’s work has been recognized for bridging theoretical neuroscience and applied engineering, earning him a reputation as a rising star in the field. For students and researchers, his studies offer a compelling blueprint for designing intelligent, low-power robotic systems, directly addressing challenges in industrial automation, search-and-rescue, and autonomous vehicles.