AIR Distinguished Speaker Series: James Zou, Associate Professor, Stanford University

Date: March 27, 2024
Time: 1 – 2 PM ET 
Location: BU Center for Computing & Data Sciences, 665 Commonwealth Ave, Room 1101
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Co-Sponsored by the Machine Learning in Medicine (MLxMED) Series. To learn more about the MLxMED Seminar series view here: Machine Learning in Medicine.

Speaker: James Zou, Associate Professor of Biomedical Data Science, Computer Science (CS) and Electrical Engineering (EE), Stanford University

Talk Title: Biomedicine in the age of generative AI

Abstract: This talk will investigate how we can use generative AI to help researchers, clinicians, and patients as well as some of the fundamental technical challenges.

Biography: James Zou is an Associate Professor of Biomedical Data Science, Computer Science (CDS) and Electrical Engineering (EE) at Stanford University. He is also the faculty director of Stanford AI4Health. 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. 

Faculty Host:  Kayhan Batmanghelich, Assistant Professor, ECE

About MLxMed Seminar Series:: Medicine is complex and data-driven and discovery and decision making are increasingly enabled by machine learning. Machine learning has the potential to support, enable and improve medical discovery and clinical decision making in areas such as medical imaging, cancer diagnostics, precision medicine, clinical trials, and electronic health records. This seminar series focuses on new algorithms, real-world deployment, and future trends in machine learning in medicine. Learn more on the MLxMed website: https://ml-in-medicine.org/

The MLxMed Seminar Series is hosted by the Department of Biomedical Informatics, University of Pittsburgh; the Hariri Institute for Computing, Boston University; and the University of Toronto