-Designed an AI system utilized for Automated Optical Inspection (AOI) in notebook inner components. -Developed an end-to-end AI ecosystem, including AI data annotation system, AI model training system, and AI model deployment system with front-end, back-end, and SQL Server integration. -Led a team of 3 code members responsible for daily maintenance tasks of the AI AOI system across 42 production lines in 5 Compal plants. -Achieved a 30% reduction in the cycle time of AI model training by optimizing the size of AI model files and incorporating broken image detection. -Engineered automated tools to replace manual AI system operations, resulting in a 70% increase in efficiency and a significant reduction in human error. -Developed 7 web APIs for PostgreSQL, cutting down the time for Non-Technical Failure (NTF) analysis by 50% and simplifying the management of the AI model tracking system. -Enhanced the AI data annotation system by implementing label hot keys for 40 customized label items, leading to a 30% improvement in labeling efficiency.

-Spearheaded the design of test systems for IoT products on manufacturing lines, successfully applied to 37 IoT products, including smart meters, smart gym machines, and medical equipment, for quality monitoring and functional testing. -Collaborated closely with manufacturing teams and customers to enhance the ODM production process. -Developed instrument control programs for various measuring instruments, enabling programmatic control for smart manufacturing, encompassing digital power meters, Keysight Generators, and Anritsu RF instruments. -Led the development of the function testing program for the smart home gym machine (Tonal) and defined testing specifications for board function and assembly function. -Engineered automated tools for customers to analyze ME BOM data, data reports, document software operations, or carry out daily tasks automatically, resulting in a 75% reduction in workload, a 50% decrease in human error, and a 91% improvement in project efficiency. -Established the first automatic electromagnetic compatibility test system for EMC testing, integrating ABB robot, electrostatic discharge device, and image recognition to boost compatibility test efficiency, minimize processing errors, improve measurement accuracy by 30%, reduce measurement time by 50%, and operate continuously for 24 hours with robot arms.

-Successfully implemented Google Compatibility Test Suite, ensuring the Android system's compliance with compatibility standards. -Designed and executed automated tests using Android API, resulting in a notable reduction of over 50% in system test time. -Maintained a meticulous approach to testing, creating detailed test cases and ensuring a high level of quality assurance for mobile systems.