March 26 lecture will explore use of medical AI in placenta analysis

UNIVERSITY PARK, Pa. — The Penn State Center for Socially Responsible Artificial Intelligence (CSRAI) will host Yimu Pan, a doctoral candidate in the College of Information Sciences and Technology, as part of its Young Achievers Symposium. Pan’s talk, titled “Cross-Modal Learning and Foundational Models in Medical AI: From Techniques to Applications in Placenta Analysis,” will discuss how artificial intelligence (AI) can improve medical care by combining different types of data, such as medical images and clinical notes. 

The talk will take place from 3 to 4 p.m. on Wednesday, March 26 in E202 Westgate Building on the University Park campus and will also be accessible via Zoom. 

According to Pan, AI models that are trained on large amounts of data can find patterns and improve how doctors diagnose and treat health issues. A key focus of the lecture will be how AI can improve placenta analysis — an important but often overlooked area of prenatal care. By combining medical images with clinical notes, AI can help doctors better predict and manage pregnancy complications. Pan will also discuss how generative models, which create realistic medical images and data, can help fill in gaps when real-world data is limited. 

Pan’s broader research focuses on computer vision and multimodal learning, with applications in health care, emotion understanding and AI-assisted clinical decision-making. He previously worked as an applied scientist intern at Amazon, where he collaborated on projects related to last mile delivery optimization. 

This talk is part of CSRAI’s Young Achievers Symposium, which highlights early career researchers in diverse fields of AI for social impact. CSRAI promotes high-impact, transformative AI research and development, while encouraging the consideration of social and ethical implications in all such efforts. The center supports a broad range of activities from foundational research to the application of AI to all areas of human endeavor.