Mohd Wajid

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About

Mohd Wajid is an emerging researcher specializing in embedded systems, radar signal processing, and machine learning applications for intelligent sensing systems. His work sits at the intersection of hardware implementation and real-world perception tasks, with a particular focus on advancing autonomous and assistive technologies. Wajid's most notable contributions center on FPGA-based systems for real-time object detection and range estimation using Frequency-Modulated Continuous Wave (FMCW) millimeter-wave radar — technologies critical to Advanced Driver Assistance Systems (ADAS) and robotics. His 2024 paper on this topic has already garnered 15 citations, reflecting strong community interest, while his 2025 follow-up leveraging the PYNQ-ZU Zynq UltraScale+ MPSoC platform demonstrates his continued push toward practical, deployable hardware solutions with 8 citations in its early circulation. Beyond radar systems, Wajid has contributed to acoustic signal processing, proposing a Support Vector Regression-based Direction of Arrival (DOA) estimation technique for acoustic sources — applicable to surveillance, robotics, and defense — earning 7 citations since 2020. Together, his body of work reflects a researcher committed to bridging advanced signal processing algorithms with real-time hardware implementations, making meaningful contributions to intelligent sensing and autonomous systems research.