Devin Jiang

Master of Science student at Arizona State University specializing in Artificial Intelligence and Machine Learning. Proven success in both developing AI-driven analysis systems and modernizing lab automation. Experience includes spearheading an AI-powered Smart Search project for document analysis and re-architecting a parametric bench tester with Python, which included implementing live data plotting, automated reporting and analysis, and advanced failure safety system.

Microchip Professional Projects

• Co-authored several patent applications integrating novel AI/ML systems with hardware systems.
• Led the development of an AI-driven RAG system(s), "Smart Search," to analyze reliability documents and ISTFA papers, as well as FA reports for automating failure report analysis to significantly reduce time to insights.
• Architected a future version of Smart Search to incorporate a Multi-Agent and MCP Workflow for advanced summarization and trend plotting capabilities.
• Lead Designer of the architecture for a future AI tool to extract data from internal PDF qualification reports and generate redacted, customer-friendly reports.
• Spearheaded the modernization of the Reliability Bench Tester by converting the legacy automation system from LabVIEW to Python, which enhanced test throughput, data processing efficiency, code maintainability and modularity.
• Increased Reliability Bench Tester system reliability and usability by implementing a consolidated user interface with live, real-time data plotting and engineering the test sequence to continue uninterrupted even if an individual device fails.
• Designed and built an automated data analysis and reporting tool for Reliability Bench Tester that transforms raw test results into actionable summaries and delivers them directly to stakeholders via Microsoft Teams to enable faster, data-driven decision-making.

AI-Powered Sales & Inventory Analytics Application (Personal Project)

• Architected and developed a full-stack inventory management system to track sales operations, quantities, and pricing, featuring multiple tabular data views.
• Engineered an intelligent pricing suggestion feature using an AI agent with tool-calling capabilities to perform real-time web research and calculate average market prices for items.
• Implemented an interactive data visualization dashboard to generate plots and graphs for key metrics such as ROI, profit margins, and inventory turn-time, enabling clear, data-driven business insights.
• Tech Stack: Python, Pandas, Tkinter, Matplotlib, Gemini API, Web tools