Shubh Goel

Papers

Total Citations

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About

Shubh Goel is a rising researcher at the intersection of computer vision, hardware acceleration, and real-time imaging systems. His work focuses on developing efficient, hardware-based solutions for computationally intensive image analysis tasks, particularly contour tracing—a fundamental technique in medical imaging, robotics, and machine learning. In his most cited work, "A Hardware Accelerator for Contour Tracing in Real-Time Imaging" (2024), Goel introduced a novel accelerator based on adapted and segmented vertex following and run-data-based-following methods, achieving significant speedups over software implementations. This contribution addresses the growing demand for low-latency, high-throughput vision systems in edge computing and embedded platforms. With early citations already recognizing the practical impact of his design, Goel’s research bridges the gap between algorithmic innovation and hardware efficiency. His work is particularly relevant for applications requiring real-time object boundary detection, such as autonomous navigation and medical diagnostics. As an emerging scholar, Goel is establishing a reputation for creating scalable, hardware-aware solutions that push the boundaries of real-time image processing.