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Generative AI for Biomedicine.
Iribe Center, Room 3137 (Zoom link: https://umd.zoom.us/j/97287503999)
Thursday, February 9, 2023, 2:00-3:00 pm Calendar
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I will explore how generative AI can improve biomedicine. I first show how generative models can augment human creativity by discussing a project discovering new antibiotics. We used a generative model to create structurally novel molecules for drug-resistant bacteria. A benefit of our approach is that the molecules are designed to be easy to synthesize, and we experimentally tested and validated our antibiotics. Then I will discuss how to use generative AI to uplevel cheap biomedical data into expensive and difficult-to-collect data. Finally, I will give an example of using generative model to design complex protocols with multiple tradeoffs–clinical trials.  


James Zou is an assistant professor of Biomedical Data Science, CS and EE at Stanford University. He develops machine learning methods for biology and medicine. He works on both improving the foundations of ML–-by making models more trustworthy and reliable–-as well as in-depth scientific and clinical applications. 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, Tencent and Adobe.

This talk is organized by Erin Molloy