Scholar
James Zou
Google Scholar ID: 23ZXZvEAAAAJ
Stanford University
Machine learning
computational biology
computational health
statistics
biotech
Follow
Homepage
↗
Google Scholar
↗
Citations & Impact
All-time
Citations
51,141
H-index
95
i10-index
313
Publications
20
Co-authors
0
Contact
CV
Open ↗
Twitter
Open ↗
Publications
128 items
PaperDoctor: Evidence-Grounded and Actionable Feedback for Scientific Papers in Progress
2026
Cited
0
LabAgent: Customize Any Research Hubs for Scientific Discoveries Using AI Agents
2026
Cited
0
Learning transferable human physiology from two million hours of sleep with SleepFM-2
2026
Cited
0
Language-encoded network topology enables large language models to reason about complex networks
2026
Cited
0
Physics of Agents: Statistical Mechanics Predicts Collective Behavior of AI Agents
2026
Cited
0
Conversation as Measurement in Clinical Encounters: Observable Phase Structure, Partially Observable Patient State
2026
Cited
0
Fisher-R1: Training LLM Agents for Reliable Hypothesis Testing
2026
Cited
0
string2string Studio: An Interactive, In-Browser Platform for String-to-String Algorithms
2026
Cited
0
Load more
Resume (English only)
Academic Achievements
Two-time Chan-Zuckerberg Investigator
Recipient of the Sloan Fellowship
Recipient of the NSF CAREER Award
Awarded AI research grants from Google, Amazon, and Adobe
Recipient of the Overton Prize (2025)
Paper 'CollabLLM' won the ICML Outstanding Paper Award (6 out of >12K submissions)
Published extensively in top journals including Nature, Nature Methods, Nature Communications, Science, Cell, NEJM AI, PNAS, and JMLR
EchoNet AI received FDA clearance
Published numerous papers at top conferences including ICML, NeurIPS, ICLR, and AISTATS
Developed key tools/frameworks including TextGrad, InterPLM, TISSUE, SyntheMol, and 7-UP
Background
Associate Professor of Biomedical Data Science at Stanford University, with courtesy appointments in Computer Science and Electrical Engineering
Focuses on making machine learning more reliable, human-compatible, and statistically rigorous
Especially interested in applications of ML in human disease and health
Several of his team's algorithms are widely used in tech and biotech industries
Member of the Stanford AI Lab
Faculty director of the university-wide Stanford Data4Health hub
Co-authors
0 total
Co-authors: 0 (list not available)