Summary
Rujun Han is a research scientist with a CS PhD specializing in natural language processing and machine learning, and nine years of industry experience applying research to production AI services. Currently at Google after contributing to AWS AI products, he led research on RAG QA, LLM evaluation, and controllable generation for Kendra and Amazon Q for Business. His background spans financial and enterprise domains—from the Federal Reserve Bank of New York to Commonwealth Bank—bringing rigor in evaluation and real-world constraints to model design. Trained at USC and NYU with an economics BA from Hamilton College, he blends strong theoretical foundations with practical data-science instincts. Known for translating cutting-edge research into customer-facing features, he also carries experience across both research and applied scientist roles that bridge labs and large-scale systems. Based in Guangzhou, he pairs global collaboration experience with a track record of shipping evaluated, controllable NLP systems.
9 years of coding experience
3 years of employment as a software developer
Doctor of Philosophy - PhD Computer Science, Doctor of Philosophy - PhD Computer Science at University of Southern California
Master of Science (M.Sc.) Data Science, Master of Science (M.Sc.) Data Science at New York University
Bachelor of Arts (B.A.) Economics, Bachelor of Arts (B.A.) Economics at Hamilton College
Data Mining, Data Mining at Columbia University
Chinese, English