Summary
Min Sun is a PhD candidate at Stanford and a student researcher at Google DeepMind with nine years of experience building machine learning models for biomedical applications. She specializes in biomedical vision-language models and curating large-scale open datasets to make AI in healthcare reproducible, generalizable, and clinically actionable, with a focus on precision oncology. Her work spans academic research at Stanford SAIL and industry collaborations, including internships at Hugging Face, Guardant Health, and prior data science roles at Invitae where she automated NGS lab workflows. Min combines deep technical skills in ML with practical experience deploying health-focused foundation models and designing algorithms for cfDNA methylation data. She has a dual BS/BA in Statistics and Economics from UCLA and is notable for translating complex biomedical signals into usable tools for clinical research. Based in Palo Alto, she balances rigorous research with open-source-minded engineering to accelerate trustworthy medical AI.
9 years of coding experience
4 years of employment as a software developer
University of California, Los Angeles
Doctor of Philosophy - PhD, Biomedical Data Science, Doctor of Philosophy - PhD, Biomedical Data Science at Stanford University
English, Korean