Summary
Kang Han is a Software QA Analyst and recent University of Michigan summa cum laude computer science graduate based in Irvine, CA, combining a strong academic foundation with ten years of practical experience in software and AI-focused roles. He specializes in evaluating and debugging AI-generated code, creating structured annotation schemas, and designing evaluation rubrics that improve model reliability and developer feedback loops. Prior internships show hands-on backend and ML work—building secure Node.js/AWS Lambda auth flows, implementing transcript summarization and PII masking for real-time systems, and coordinating small research teams. His tutoring and team-lead experience reflect clear communication skills and an ability to translate complex technical concepts for diverse audiences. Known for a "do one thing, do it best" ethos, Kang brings attention to detail and a methodical approach that benefits both code quality and dataset curation. He is actively seeking full-time opportunities in software or web development where his QA/ML tooling experience can accelerate robust product delivery.
10 years of coding experience
1 year of employment as a software developer
Bachelor's degree, Computer Science, 3.82/4.00 - Summa Cum Laude, Bachelor's degree, Computer Science, 3.82/4.00 - Summa Cum Laude at University of Michigan
High School Diploma, 4.00, High School Diploma, 4.00 at Arnold O. Beckman High School