Summary
Zhili Feng is a researcher and machine learning practitioner with a decade of experience focused on large language models, privacy, memorization, robustness, and model adaptation. Transitioning from a PhD at Carnegie Mellon to a researcher role at OpenAI, Zhili combines deep theoretical work with practical system-building from internships at Microsoft, Amazon, and Facebook. His background spans online learning theory, tokenization and compression, and better training algorithms—skills reinforced by earlier full‑stack and research projects in temporal reasoning and BIM visualization. Based in Pittsburgh, he balances rigorous research with a disciplined, everyday workout mentality that he credits for sustained productivity.
10 years of coding experience
5 years of employment as a software developer
Lyndon Institute
Master of Science - MS Computer Science, Master of Science - MS Computer Science at University of Wisconsin-Madison
BACHELOR OF SCIENCE Computer Science, BACHELOR OF SCIENCE Computer Science at University of Illinois Urbana-Champaign
Doctor of Philosophy - PhD Machine Learning, Doctor of Philosophy - PhD Machine Learning at Carnegie Mellon University
English, Chinese