Led a 4-member engineering team to develop an AI-powered writing assistant using Retrieval-Augmented Generation (RAG), delivering real-time feedback in under 5 seconds with 80% accuracy. Directed the design and integration of a RAG pipeline, improving contextual accuracy and reducing error rates by 25% through standardized data preprocessing and indexing. Coordinated 50+ prompt engineering experiments, boosting generative AI response quality and consistency across test datasets. Oversaw the implementation of semantic search infrastructure with Qdrant, supporting 1,000+ query tests for contextual retrieval. Managed deployment processes by organizing Docker and Jenkins automation efforts, cutting deployment time by 40% and reducing integration failures by 30%.

Research Intern at Shanghai Jiao Tong University

September 1, 2023 - September 1, 2023

Designed and developed a Diagnostic Report Management System that streamlined CT scan scheduling and reporting, reducing appointment processing time by 35%. Created UML diagrams (swim lane, use case, class) to map 10+ user interactions and workflows, ensuring technical clarity for developers and stakeholders. Implemented a PHP/MySQL backend with an HTML/CSS frontend, enabling secure file uploads and appointment management for 100+ test users during evaluation. Conducted usability testing with patients and staff, achieving a 20% improvement in accessibility scores and positive feedback on efficiency. Documented system architecture, validation logic, and innovations in a 20+ page defense report and contributed to a published paper.