This workshop aims to demystify federated learning (FL) and showcase its transformative potential in biomedicine and healthcare. From core principles to real-world applications, participants will explore how FL enables collaborative AI development across institutions, without compromising data privacy. We’ll examine case studies spanning medical domains, dive into ethical and regulatory considerations, and highlight emerging paradigms like personalized FL. The day will close with an industry panel and demo session. By fostering interdisciplinary dialogue, we aim to build a shared foundation—and spark momentum toward a federated learning infrastructure at Columbia.
Learn more about the workshop and the speakers at the event.
This event is for clinicians, biomedical researchers, biomedical informaticists, computer scientists, data scientists, engineers, data privacy experts, IT and IRB leaders, and industry professionals. Whether you’re FL-curious or already federating in the wild, this is your chance to learn, challenge assumptions, and connect with others working to advance privacy-preserving AI in biomedicine and health.
