T. Andrew Yang

Papers

Total Citations

H-Index

About

T. Andrew Yang is a researcher whose work bridges embedded systems, computer vision, and autonomous vehicle technologies. His key contributions center on developing efficient, low-cost hardware solutions for real-time image processing, particularly in the context of autonomous navigation. His most cited paper, "An Edge Detection IP of Low-Cost System on Chip for Autonomous Vehicles" (2021), demonstrates a novel approach to integrating edge detection algorithms directly onto system-on-chip (SoC) architectures, reducing computational overhead and power consumption for resource-constrained autonomous platforms. This work, with 4 citations, highlights his focus on practical, deployable solutions that balance performance with affordability. Yang’s research is notable for its emphasis on hardware-software co-design, enabling real-time visual processing in vehicles without reliance on expensive, high-power GPUs. His contributions are particularly relevant for students and engineers seeking to understand how edge computing can enhance safety and efficiency in autonomous systems. By prioritizing cost-effective implementations, Yang’s work helps democratize access to advanced driver-assistance technologies, making them viable for broader applications in robotics and smart transportation.