Summary
Daniel Guo is a researcher and software engineer combining six years of experience at the intersection of AI and biology, currently working on genomic foundation models at Arc Institute while pursuing MS Computer Science (AI) at Stanford. He brings hands-on research and product experience from roles at Stanford SAIL, Apple FaceTime, and Identifeye Health, plus early-stage investing and digital health app development. His work spans model-driven bioinformatics, test-time compute for LLM guidance, and AI-enabled medical imaging, reflecting a rare fluency across wet-lab biology and scalable ML systems. Daniel has led applied projects in tele-endocrinology and photoactivatable CRISPR base editors, showing an ability to move concepts from bench to deployable software. Based in Palo Alto, he balances academic research with industry internships (including Meta) and venture diligence, signaling both technical depth and product intuition. Colleagues describe him as a pragmatic researcher who translates biological insight into robust engineering solutions.
6 years of coding experience
2 years of employment as a software developer
Dogwood Diploma, Dogwood Diploma at St. George's School
Master of Science - MS Computer Science (AI), Master of Science - MS Computer Science (AI) at Stanford University
English, French, Latin, Chinese