Jingwen Zheng

University of Science and Technology of China, National Cheng Kung University

Papers

Total Citations

H-Index

About

Jingwen Zheng is a researcher whose work spans autonomous systems and semiconductor yield enhancement, demonstrating versatility across robotics and industrial optimization. In robotics, Zheng’s most cited paper, “The Architecture of a Driverless Robot Car Based on EyeBot System” (2019, 5 citations), presents a comprehensive system architecture for an autonomous model vehicle designed for the Carolo-Cup competition. This work details the integration of perception, control, and navigation on the EyeBot platform, contributing practical insights into low-cost autonomous driving platforms. In the domain of semiconductor manufacturing, Zheng’s paper “Blind-Stage Search Algorithm for the Key-Variable Search Scheme” (2017, 4 citations) addresses the critical challenge of yield enhancement. By proposing a novel algorithm for identifying root causes of yield loss during development and mass production, this work offers a cost-saving approach to improving profitability in semiconductor fabrication. Though Zheng’s citation counts are modest, these contributions reflect focused, application-driven research in two distinct fields. The driverless car architecture paper showcases hands-on engineering for competitive robotics, while the yield enhancement work targets real-world industrial efficiency. Together, they highlight Zheng’s ability to tackle complex problems from hardware-software integration to data-driven optimization.