Alamgir Naushad

National University of Sciences and Technology

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About

Alamgir Naushad is a rising researcher at the forefront of autonomous robotics and intelligent navigation systems. His work centers on developing robust perception and decision-making algorithms that enable robots to operate safely in complex, dynamic environments. Naushad’s key contributions lie in sensor fusion, particularly the integration of LiDAR and camera data, and the application of reinforcement learning—specifically Proximal Policy Optimization (PPO)—to enhance real-time navigation. His most-cited paper, "Proximal Policy Optimization Based Autonomous Navigation in Dynamic Environment Using LiDAR-Camera Fusion Technique" (2025), has already garnered 2 citations, signaling early impact in this fast-evolving field. By addressing the critical challenge of safe autonomous movement in unpredictable indoor settings, Naushad is helping bridge the gap between theoretical robotics and practical deployment. His work holds promise for applications in service robotics, warehouse automation, and assistive technologies, making him a researcher to watch as he continues to advance the capabilities of intelligent, self-navigating machines.