Speaker: James Zou, Stanford University

AI Agents for Scientific Discoveries

This talk will explore how generative AI agents can enable scientific discoveries through three interconnected vignettes. First, James Zou will discuss how generative AI can expand researchers' creativity by designing and experimentally validating new small-molecule drugs. Next, he'll introduce the Virtual Lab—a collaborative team of AI agents conducting in silico research meetings, supported by real-world experiments, to design new nanobodies. Finally, Zou will investigate how language model agents can provide constructive feedback on research projects and peer reviews.

James Zou is an associate professor of Biomedical Data Science and, by courtesy, of CS and EE at Stanford University. He works on advancing the foundations of ML and in-depth scientific and clinical applications. Many of his innovations are widely used in tech and biotech industries.  He has received a Sloan Fellowship, an NSF CAREER Award, two Chan-Zuckerberg Investigator Awards, a Top Ten Clinical Achievement Award, several best paper awards, and faculty awards from Google, Amazon, and Adobe. His research has also been profiled in popular press including the NY Times, WSJ, and WIRED.

About the Seminar Series

Stanford Data Science (SDS) is organizing a scientific seminar series, normally scheduled on the first Wednesday of the month. To provide some cohesiveness to the events and to ensure that over time we can explore the diverse topics that fit over the data science umbrella, we plan to identify an overarching theme for each academic year. During 2024-25 the theme for the seminar series is "Scientific Discovery in the Age of Data and AI.”

Scientific Discovery in the Age of Data and AI

The last few years have seen a substantial increase in the reported success of machine learning (ML), and generative artificial intelligence (AI). These impact practices in delivering services from financial institutions to entertainment and medicine. However scientific research also increasingly relies on large data sets, whose analysis leverages ML/AI. This seminar series aims to investigate if and how the paradigm for scientific research has changed or should change to incorporate these new tools and the possibilities they open.

A diverse group of scholars engaged in scientific research, method development, and historical and epistemological investigations will give a 50-minute presentation, followed by discussion.

The event is open to the Stanford Community. Stanford students and postdocs have the opportunity to engage more directly with speakers and topics by enrolling in the Canvas course here.

Speakers in the series include Ellen Zhong (Princeton), Tom Griffiths (Princeton), Thomas Icard (Stanford), and Jure Leskovec (Stanford) among others.