Muhammad Azri Yahya

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About

Muhammad Azri Yahya is a researcher at the forefront of autonomous vehicle perception, with a primary focus on integrating deep learning with LiDAR-based sensing systems. His most-cited work, "Object Detection for Autonomous Vehicle with LiDAR Using Deep Learning" (2020, 21 citations), addresses a critical limitation in autonomous driving: the degraded performance of camera-based visual perception in low-light conditions. By proposing a deep learning algorithm tailored for LiDAR data, Yahya demonstrates how 3D point cloud processing can maintain robust object detection when traditional cameras fail, thereby enhancing vehicle safety and reliability. This contribution is particularly significant as the industry moves toward sensor fusion for Level 4 and Level 5 autonomy. Yahya’s research bridges the gap between theoretical deep learning architectures and practical deployment challenges, offering a scalable solution for real-world driving environments. His work has been cited by researchers exploring multi-modal perception systems and has influenced subsequent studies on LiDAR-camera fusion. Through this foundational paper, Yahya has established himself as a key voice in advancing perception robustness, making his research essential reading for students and engineers working on autonomous vehicle safety systems.