★★ Considering the weather and transportation conditions, and for the safety of all participants, the lecture originally scheduled for tomorrow will be postponed. A new registration form will be opened, and further announcements will be made accordingly. ★★

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This lunchtime lecture series blends innovation, expertise, and a relaxed atmosphere, offering an exploration of the latest applications and future advancements of artificial intelligence in digital medicine. While enjoying a delicious lunch, participants will gain cutting-edge insights into AI in medicine and engage in in-depth discussions with experts.

Speakers:

• Yu-Shuen Wang ( Professor, Institute of Data Science and Engineering, National Yang Ming Chiao Tung University )

Normalizing Flows (NFs) can precisely map simple base distributions to complex real-world data while enabling accurate likelihood estimation—something that is often difficult for other models to achieve.

This talk will introduce the core concepts and advantages of NFs, and share our recent research on their practical applications in tasks such as graph coloring, badminton shuttle landing prediction, and classification with noisy labels. In addition, we will briefly highlight the potential and breakthroughs of NFs in biomedical fields, including medical image analysis and drug molecule design, demonstrating their innovative value across disciplines.  

We welcome all colleagues interested in AI and medical innovation to sign up and explore the limitless possibilities of smart medicine together!

【Lecture Information】

•  Topic: Exploring Normalizing Flows and Their Diverse Applications 
•  Date & Time: November 12, 2025 (Wed.) | 12:10-13:20 (Temporarily canceled; the rescheduled date will be announced later.)
•  Venue: Room IR630, 6th Floor, International Academic Research Building, Kaohsiung Medical University
•  Organizers: Biomedical Artificial Intelligence Academy of KMU, Medical AI Innovation and Application Center of KMUH, Teaching and Learning Development and Resource Center KMU
•  Additional Info: Lunch will be provided for in-person attendees. 

※ This lecture is eligible for KMU faculty growth credits. Participants must complete both sign-in/out and the satisfaction survey to receive credit points.

We look forward to your participation!