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What: Virtual lecture series on topics across machine learning in medicine, featuring extensive Q & A and panel discussions

Why: To reduce academia’s carbon footprint, accommodate the schedules of the world’s top scientists and maintain social distancing

Who: All are welcome!

Where: Zoom Webinar

Recordings of previous talks can be found here.

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Sang Hyun Park, PhD
Associate Professor, Department of Computer Science and Engineering, POSTECH
When: Friday, May 22, 2026,11am-12pm Eastern Time​​

Title: Toward Generalizable Medical AI under Limited Annotation and Privacy Constraints

Abstract: Artificial intelligence has shown great promise in medical image and healthcare data analysis. However, real-world medical datasets often suffer from limited annotations, heterogeneous data distributions across institutions, and strict privacy constraints that prevent centralized data sharing. These challenges make it difficult to directly apply conventional supervised learning methods that rely on large-scale, fully labeled datasets. In this talk, I will introduce recent approaches for developing robust AI systems that can effectively learn from weakly labeled and heterogeneous medical data. The presentation will cover weakly supervised learning methods for leveraging imperfect clinical annotations, federated learning frameworks that enable collaborative model training without sharing sensitive patient data, and emerging medical foundation models that learn generalizable representations from large-scale medical datasets. I will also discuss recent advances in instruction-free tuning strategies that allow foundation models to adapt to new medical tasks with minimal supervision. Together, these approaches aim to enable scalable and trustworthy AI solutions for real-world healthcare environments.

Bio: Dr. Park is an Associate Professor in the Department of Computer Science and Engineering at POSTECH. His research focuses on medical artificial intelligence, particularly in multimodal learning, weakly supervised learning, federated learning, and foundation models for healthcare applications. Prior to joining POSTECH, he served as a tenured faculty member at DGIST from February 2017 to February 2026. He completed postdoctoral training at SRI International and at the Biomedical Research Imaging Center at the University of North Carolina. Prof. Park received his Ph.D. from Seoul National University in 2014 and his B.S. from Yonsei University in 2008.
Pietro Gori, PhD
Professor in Artificial Intelligence and Medical Imaging, Télécom Paris
When: Friday, May 29, 2026,11am-12pm Eastern Time​​

Title: TBD

Abstract: TBD

Bio: TBD
Ninon Burgos, PhD
Research Director, CNRS, Paris Brain Institute
When: Friday, June 5, 2026,11am-12pm Eastern Time​​

Title: TBD

Abstract: TBD

Bio: TBD

We are currently inviting speakers for 2026! If you are interested or would like to nominate a speaker, please email Dr. Qingyu Zhao at qiz4006 at med dot cornell dot edu

© 2023 by SCALE IT UP. Proudly created with wix.com For Questions: Contact Qingyu Zhao at qiz4006 at med dot cornell dot edu

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